1 Background

This report shows the analysis performed for 16S rRNA gene amplicon sequencing from the gut microbiome of 148 pregnant women. For each pregnant woman, samples were taken at different time points (i.e. from 1 to 3 different time points per woman) during the pregnancy (i.e. up until day ~280 when the child is born) to give a total of 377 samples. From the 148 pregnant women, 92 are diabetic (T1D) and 56 are healthy (nonT1D). Samples from the different women were NOT taken in the exact same Day in pregnancy, thus Day should be treated as a continuous variable rather than a categorical. However, time points could be categorised into trimesters if necessary, correspondence being:

Trimester 1 = 0-99 days

Trimester 2 = 100-196 days

Trimester 3 = 196-280 days

Summary:

145 pregnancies: 94 in T1D women and nonT1D=56 in wome without T1D (non-T1D).

A total of 139 women donated samples, 6 women donated samples from 2 different pregnancies giving a total a 145 pregnancies.

1-3 time points per woman per pregnancy (from day 37 to day 274 of the pregnancy).

354 samples in total: T1D=235 and nonT1D=119.

For the analysis we would explored if there is a difference in Alpha and Beta diversity between T1D and nonT1D. Furthermore, we would also identified differentially abundant operational taxonomic units (i.e. OTUs or sequence variants of the 16S rRNA that are roughly equivalent to a bacterial species) between T1D and nonT1D pregnant women.

Sample details information:

Samples were generated by PCR amplification from stool samples targeting the V4 region of the 16S rRNA gene. Each sample was sequenced twice on different sequence wells (i.e. technical sequencing replicates) from the Illumina MiSeq instrument with the paired-end 600-cycle (2 × 300) kit. Samples were sequenced in 6 different sequencing runs. Samples from the same pregnant woman at different time points were sequenced in the same run.

2 Data generation

2.1 Processing the sequences: from sequence data to feature table

The data was processed through Qiime2 (https://qiime2.org/) which is a next-generation microbiome bioinformatics platform written in python. The analysis starts with raw DNA sequencing data with the following steps and python commands that were performed for each sequencing runs separately:

  1. Import paired-end sequencing data into qiime2.
  • command: qiime tools import –type EMPPairedEndSequences –input-path ./1-Run/ –output-path ./1-Run/1-Run_MISEQXXXX.qza
  1. Demultiplex data to know which sample each paired-end reads belong to.
  • command: qiime demux emp-paired –m-barcodes-file metadata.tsv –m-barcodes-category BarcodeSequence –i-seqs 1-Run_MISEQXXX.qza –o-per-sample-sequences demux –p-rev-comp-mapping-barcodes
  1. Trimming PCR primers: Search demultiplexed paired-end sequences for adapters and remove them. In this step everything from the amplification primers on is removed.
  • command: qiime cutadapt trim-paired –i-demultiplexed-sequences ./demux.qza –p-front-f GGACTACNVGGGTWTCTAAT –p-front-r GTGYCAGCMGCCGCGGTAA –o-trimmed-sequences trimmed_demux.qza –verbose

The demultiplexed data resulting from this step was uploaded to the short read archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra/) with accession number PRJNA604850.

  1. Sequence quality control and feature table construction. In this step qiime2 uses the software Divisive Amplicon Denoising Algorithm 2 (DADA2; https://www.nature.com/articles/nmeth.3869), a quality-aware model-based approach for correcting Illumina amplicon errors. Sample composition is inferred by dividing amplicon reads into partitions consistent with the error model. DADA2 does not create OTUs (i.e. cluster sequences to a given % identity threshold) and does differentiate closely related ribosomal sequence variants (i.e. RSV or features). The complete DADA2 pipeline integrated in qiime2 implements sample inference, chimera identification, merging of paired-end reads and the creation of a “feture-per-sample counts table”.
  • command: qiime dada2 denoise-paired –i-demultiplexed-seqs trimmed_demux.qza –o-table table –o-representative-sequences rep-seqs –p-trunc-len-f 230 –p-trunc-len-r 160 –p-max-ee 3 –p-n-threads 8

The 6 runs where processed with the same parameters, including trimming of the forward reads to 230 basepairs and the reverse reads to 160 bp (i.e. parameters –p-trunc-len-f 230 and –p-trunc-len-r 160) and number of expected errors higher than 3 (–p-max-ee 3). Although these parameters should be different for different sequencing runs (depending on their quality), we used the same parameters for the 6 runs (i.e. parameters from the poorest quality run were used) in order to be able to merge the resulting 6 feature tables into 1. The feature ids in the resulting tables are presented as hashes of the sequences defining each feature. The hash will always be the same for the same sequence so this allows feature tables to be merged across runs of this method. You should only merge tables if the exact same parameters are used for each run.

  1. The 6 tables were merged:
  • Command to merge feature tables: qiime feature-table merge –i-tables table_Mother_1-Run.qza –i-tables table_Mother_2-Run.qza –i-tables table_Mother_3-Run.qza –i-tables table_Mother_4-Run.qza –i-tables table_Mother_6-Run.qza –i-tables table_Mother_7-Run.qza –o-merged-table table_Mother_All-Runs.qza

  • Command to merge representative sequences: qiime feature-table merge-seqs –i-data rep-seq1.qza –i-data rep-seq2.qza –i-data rep-seq3.qza –i-data rep-seq4.qza –i-data rep-seq6.qza –i-data rep-seq7.qza –o-merged-data rep-seq_Allmerged.qza

Information on which samples were sequenced in which run can be found in supplementary excel file E0. If the processing using DADA2 (within Qiime2) needs to be repeated, sequences from the different sequencing runs must be processed separatelly and then the resulting tables and representative sequences must be merged previous to analysis with phyloseq.

  1. The taxonomic classification was done using the resulting representative sequences with the following Qiime2 command:
  • qiime feature-classifier classify-sklearn –i-classifier /home/$YourPath/Naive_Bayes_classifiers/silva-119-99-515-806-nb-classifier.qza –i-reads rep-seq_Allmerged.qza –o-classification taxonomy_AllMerged.qza
  1. A phylogenetic tree was build within Qiime2 as follows:
  • qiime alignment mafft –i-sequences rep-seq_Allmerged.qza –o-alignment aligned-rep-seq_Allmerged.qza
  • qiime alignment mask –i-alignment aligned-rep-seq_Allmerged.qza –o-masked-alignment masked-aligned-rep-seq_Allmerged.qza
  • qiime phylogeny fasttree –i-alignment masked-aligned-rep-seq_Allmerged.qza –o-tree unrooted-tree-rep-seq_Allmerged.qza
  • qiime phylogeny midpoint-root –i-tree unrooted-tree-rep-seq_Allmerged.qza –o-rooted-tree rooted-tree-rep-seq_Allmerged.qza

Note: The phylogenetic tree was unzipped to integrated it into the phyloseq object in R. File name: Mother_All-Runs_Merged_tree.nwk

  1. A biom file containing the feature table, taxonomy and metadata was obtained from qiime2 unzipping the generated feature table and taxonomy:
  1. After unzipping table_Mother_All-Runs.qza we obtained table_Mother_All-Runs.biom, this biom file was transformed usig the software biom into a text file and then again into the correct biom format (JSON):
    • biom convert -i table_Mother_All-Runs.biom -o table_Mother_All-Runs.txt –to-tsv
    • biom convert -i table_Mother_All-Runs.txt -o table_Mother_All-Runs.biom –table-type=“OTU table” –to-json
  2. The file taxonomy_AllMerged.qza containing the taxonomy was unzipped (obtaining taxonomy_AllMerged.txt) and the header “#OTUID taxonomy confidence” was added. The format of the feature classification was also changed to obtain the greengenes format (e.g. k__Bacteria; p__XXX; c__XX, etc). After this, the biom sortware was used to add the taxonomi to the biom file: *biom add-metadata –sc-separated taxonomy –observation-header OTUID,taxonomy –observation-metadata-fp taxonomy_AllMerged.txt -i table_Mother_All-Runs.biom -o table_Mother_All-Runs_wTax.biom

  3. The metadata (i.e. per sample information for each of the variables of factors of interest) was added:
    • biom add-metadata -i table_Mother_All-Runs_wTax.biom -o table_Mother_All-Runs_wTaxMet.biom –sample-metadata-fp ./metadata_All-RunsMerged.csv
  4. The resulting file in c) was used as input into phyloseq in order to de-identify (i.e. leave no information that could associate the samples to a person in the study) the samples prior to analysis, by replacing the metadata and saving into an R object “Mothers_OTU_AFilt1_Preg.RData”.

2.2 Processing, filtering and count normalization of feature table

The resulting R object containing the feature table, sample data and taxonomy (Mothers_OTU_AFilt1_Preg.RData), the and phylogenetic tree were imported into Phyloseq (https://github.com/joey711/phyloseq), an R package used for the preprocessing, analysis and graphical display of complex 16S rRNA amplicon data that has been already processed into a feature table. In this analysis phyloseq was used for agglomerate features into OTUs. This step was performed in a separate script: Phyloseq_Mother_data_formating_w7.R. Features that were less than 0.03% different at the sequence level were agglomerated into the same OTU based on the phylogenetic tree. After this, OTUs that had a relative abundance across all samples equal or less than 0.01% were removed. This left a total of 349 OTUs across all samples. This object was saved to Mothers_OTU_Phyloseq_Obj_Filter1_w7G.RData which was used for the analysis performed in this document.

3 Bar plots taxonomy

4 Alpha diversity

Use GEEs to account for clustering due to repeated measures, and test for differences in alpha diversity between T1D and nonT1D. Include T1D x Days interaction term to test the possibility that the change in alpha diversity over time differs between T1D and nonT1D.

‘Mean-centred’ values are being used for gestational days, age and BMI were calculated. This ensures that the model coefficients presented are meaningful. The ‘geepack’ package defaults to using the empirical (robust or ‘sandwich’) estimator, which means that the estimates are robust to misspecification of the correlation structure.

4.1 Alpha diversity (T1D vs. non-T1D continuous time [Days])


Call:
geeglm(formula = Observed ~ t1dfactor * days_c + age_c + nullip + 
    bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")

 Coefficients:
                      Estimate    Std.err    Wald Pr(>|W|)    
(Intercept)          87.312304   6.321785 190.753   <2e-16 ***
t1dfactorT1D          0.598412   4.290163   0.019   0.8891    
days_c               -0.011349   0.027414   0.171   0.6789    
age_c                 0.436220   0.444266   0.964   0.3262    
nullipYes            -3.523319   3.718133   0.898   0.3433    
bmi_c                -0.619933   0.343827   3.251   0.0714 .  
HLADRXX             -11.273762   6.217263   3.288   0.0698 .  
HLAGroup3o4          -3.854993   5.107809   0.570   0.4504    
t1dfactorT1D:days_c   0.001327   0.029897   0.002   0.9646    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Estimated Scale Parameters:
            Estimate Std.err
(Intercept)      539   56.69

Correlation: Structure = exchangeable  Link = identity 

Estimated Correlation Parameters:
      Estimate Std.err
alpha   0.6766 0.05531
Number of clusters:   146   Maximum cluster size: 3 

4.2 Alpha diversity (T1D vs. non-T1D categorical time [Trimesters])


Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip + 
    bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")

 Coefficients:
                   Estimate  Std.err   Wald Pr(>|W|)    
(Intercept)         87.5304   7.5855 133.15   <2e-16 ***
t1dfactorT1D         0.7492   6.2981   0.01    0.905    
TriT2               -0.0419   5.2543   0.00    0.994    
TriT3               -0.5486   5.6430   0.01    0.923    
age_c                0.4231   0.4458   0.90    0.343    
nullipYes           -3.6292   3.7147   0.95    0.329    
bmi_c               -0.6231   0.3439   3.28    0.070 .  
HLADRXX            -11.2900   6.2120   3.30    0.069 .  
HLAGroup3o4         -3.9233   5.1262   0.59    0.444    
t1dfactorT1D:TriT2   0.2909   5.6709   0.00    0.959    
t1dfactorT1D:TriT3  -0.4055   6.0407   0.00    0.946    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Estimated Scale Parameters:
            Estimate Std.err
(Intercept)      539    56.5

Correlation: Structure = exchangeable  Link = identity 

Estimated Correlation Parameters:
      Estimate Std.err
alpha    0.676  0.0554
Number of clusters:   146   Maximum cluster size: 3 

5 OTU taxonomic level

5.1 Microbial community composition analysis at OTU level (Beta diversity analysis)

Hypothesis

Hypothesis: the gut microbiome taxonomic composition (i.e. Beta diversity) during pregnancy differs between women with and without T1D. In order to test if this hypothesis holds true, a measurement of the distance between each pair of samples is calculated (i.e. Bray-Curtis) and a repeated measure aware permutational analysis of variance (i.e. RMA-PERMANOVA) test is applied. A P-value <0.05 is considered to be significant, meaning that our hypothesis cannot be rejected. Borderline P-values are also considered positive.

Problems with the available R function for Beta diversity analysis

The current available function for performing hypothesis testing of differences in the microbiome composition between groups of samples is called Adonis (i.e. which perform a PERMANOVA test) and is part of the Rpackage vegan (Oksanen, J. et al). The main problem with this function is that if the metadata of interest does not vary with time (e.g. disease status, sex, etc.), adonis does not calculate the corresponding P value correctly, as it permutes levels within a subject. This does not make sense for something like disease status or sex as permuting within-subject will produce the exact same distribution each time you permute. This a known drawback of the adonis function for repeated measures.

In order to get the correct P-value for a time-invariant metadata, the permutation procedure has to be altered such that it permutes the subjects rather than levels within subjects, which apply to our current pregnancy dataset.

Here I’m running a script written by Jason Lloyd-Price from Curtis Huttenhower lab in Harvard. This script is being used instead of the regular Adonis (PERMANOVA test) from the R package Vegan because as stated above, our metadata of interest (i.e. T1D status) does not vary with time, we have a mixture of data which changes within and between an individual and we also have unequal group sizes (i.e. we do not always have exactly 3 samples per woman). For those three reasons, it was recommended to use his script to perform the RMA-PERMANOVA analysis.

PARAMETERS:

permute_within: This data frame has samples on rows and metadata on columns. This should only contain metadata that varies within a block (i.e. it’s a single-column data frame with only time/Days).Since, the other metadata within the block should be the same between repeated measurements and this will not hold when we introduce other factor i.e. sequencing run, BMI, parity, gestational age (i.e. Days or trimester) and conception age , those five factors should be placed here

blocks: This should just be a vector giving the group of each sample (i.e. the motherid vector; motherid is strictly accounting for personID but not for pregnancy per se).

block_data: This data frame contains per-block metadata, with one row per block (motherid). It should only contain metadata pertaining to the blocks (i.e. T1Dstatus). motherid is not numeric, ensure that the row names match the factor names in the motherid vector (blocks).

metadata_order: This is needed if you want to specify a particular order that the model should be fit in. Metadata earlier in the list will be fit and residualized first, so these should be features we are NOT interested in and want to control for.

Results from PERMANOVA test with repeat measure-aware permutations - Controlling for Days/Trimester, sequencing run, conception age, BMI, parity and HLA type

Here the blocking factor is taking into account each mother who might have given samples from different trimesters or two different pregnancies (i.e. motherid is the name of the factor). Therefore, the factor “motherid” takes into account two different pregnancies from the same mother as one SubjectID to adjust for repeated measurements

The interaction between T1D status and time was also included in order to test if the differences between T1D and non-T1D women in the same or changes throguhout pregnancy.

5.1.1 Interaction between T1D status and Time


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun                 5       3.8   0.752    2.96 0.040  0.534  
Days                   1       0.3   0.255    1.01 0.003  0.113  
T1D_Time_Interaction   1       1.0   1.023    4.03 0.011  0.078 .
Age                    1       0.7   0.697    2.75 0.007  0.770  
Parity                 1       0.7   0.655    2.58 0.007  0.909  
BMI                    1       0.5   0.482    1.90 0.005  0.316  
HLA                    2       1.1   0.557    2.19 0.012  0.406  
T1Dstatus              1       0.2   0.167    0.66 0.002  1.000  
Residuals            340      86.4   0.254         0.914  0.856  
Total                353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.078

Due to the interaction between T1D and time having a significant P-value, differences in beta diversity between T1D and non-T1D was assessed by trimester using a normal PERMANOVA with the adonis function.

Note: The function relevel was used to change the trimester used as reference in the test (e.g. when testing for differences between T2 and T3).

5.1.2 T1D status in trimester 1


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

               Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
SeqRun          3      0.90   0.299   1.145 0.062   0.17
Nulliparous     1      0.23   0.226   0.868 0.016   0.69
Age_LMP         1      0.27   0.273   1.046 0.019   0.40
BMI_conception  1      0.18   0.180   0.689 0.012   0.92
HLA.6DRML       2      0.53   0.263   1.007 0.036   0.45
T1Dstatus       1      0.33   0.331   1.269 0.023   0.14
Residuals      46     11.99   0.261         0.831       
Total          55     14.42                 1.000       
[1] 0.136

Beta diversity Plot

5.1.3 T1D status in trimester 2


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
SeqRun           4       1.4   0.361   1.354 0.042  0.022 *
Nulliparous      1       0.3   0.324   1.214 0.009  0.188  
Age_LMP          1       0.3   0.285   1.070 0.008  0.318  
BMI_conception   1       0.3   0.279   1.046 0.008  0.415  
HLA.6DRML        2       0.5   0.247   0.928 0.014  0.599  
T1Dstatus        1       0.4   0.406   1.522 0.012  0.061 .
Residuals      117      31.2   0.267         0.906         
Total          127      34.4                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.061

Beta diversity Plot

5.1.4 T1D status in trimester 3


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
SeqRun           5       2.0   0.398    1.55 0.058  0.002 **
Nulliparous      1       0.3   0.277    1.08 0.008  0.321   
Age_LMP          1       0.3   0.338    1.31 0.010  0.118   
BMI_conception   1       0.3   0.300    1.17 0.009  0.243   
HLA.6DRML        2       0.6   0.309    1.21 0.018  0.143   
T1Dstatus        1       0.5   0.546    2.12 0.016  0.005 **
Residuals      119      30.6   0.257         0.882          
Total          130      34.6                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.005

Beta diversity Plot

5.1.5 Days within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2       1.2   0.620    2.54 0.020  0.190  
seqRun      4       3.1   0.786    3.22 0.052  0.861  
Age         1       0.7   0.655    2.69 0.011  0.012 *
Parity      1       0.6   0.562    2.30 0.009  0.645  
BMI         1       0.6   0.569    2.33 0.009  0.117  
Days        1       0.1   0.126    0.52 0.002  0.497  
Residuals 224      54.7   0.244         0.897  0.173  
Total     234      61.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

5.1.6 Trimesters within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       1.2   0.620    2.53 0.020  0.200   
seqRun      4       3.1   0.786    3.22 0.052  0.839   
Age         1       0.7   0.655    2.68 0.011  0.009 **
Parity      1       0.6   0.562    2.30 0.009  0.641   
BMI         1       0.6   0.569    2.33 0.009  0.133   
Tri         2       0.3   0.141    0.58 0.005  0.708   
Residuals 223      54.5   0.244         0.894  0.239   
Total     234      61.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Note: The function relevel was used to change the trimester used as reference in the test (e.g. when testing for differences between T2 and T3).

Beta diversity Plot

5.1.7 Days within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2       1.2   0.588   2.268 0.036   0.43
seqRun      5       2.0   0.398   1.534 0.061   0.72
Age         1       0.6   0.623   2.405 0.019   0.43
Parity      1       0.5   0.462   1.783 0.014   0.74
BMI         1       0.3   0.275   1.063 0.008   0.63
Days        1       0.2   0.228   0.879 0.007   0.22
Residuals 107      27.7   0.259         0.854   0.57
Total     118      32.5                 1.000       

Beta diversity Plot

5.1.8 Trimesters within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2       1.2   0.588   2.257 0.036   0.43
seqRun      5       2.0   0.398   1.526 0.061   0.72
Age         1       0.6   0.623   2.393 0.019   0.46
Parity      1       0.5   0.462   1.774 0.014   0.74
BMI         1       0.3   0.275   1.057 0.008   0.65
Tri         2       0.3   0.174   0.666 0.011   0.80
Residuals 106      27.6   0.261         0.850   0.71
Total     118      32.5                 1.000       

Beta diversity Plot

5.1.9 Other factors

5.1.9.1 Age at conception

5.1.9.1.1 Age at conception interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2       1.2   0.605    2.38 0.013  0.290  
T1Dstatus              1       1.0   1.047    4.12 0.011  0.014 *
seqRun                 5       3.6   0.729    2.87 0.039  0.744  
Tri                    2       0.3   0.164    0.65 0.003  0.563  
Age                    1       0.7   0.739    2.91 0.008  0.387  
Parity                 1       0.6   0.623    2.45 0.007  0.933  
BMI                    1       0.5   0.497    1.96 0.005  0.432  
Age_Time_Interaction   1       0.2   0.235    0.93 0.002  0.391  
Residuals            339      86.2   0.254         0.912  0.120  
Total                353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.1.2 Age at conception interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.38 0.013   0.28   
T1Dstatus              1       1.0   1.047    4.11 0.011   0.01 **
seqRun                 5       3.6   0.729    2.86 0.039   0.74   
Tri                    2       0.3   0.164    0.65 0.003   0.53   
Age                    1       0.7   0.739    2.90 0.008   0.40   
Parity                 1       0.6   0.623    2.45 0.007   0.93   
BMI                    1       0.5   0.497    1.95 0.005   0.46   
Age_Time_Interaction   1       0.1   0.104    0.41 0.001   0.93   
Residuals            339      86.3   0.255         0.913   0.16   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.1.3 Age at conception interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.38 0.013  0.304   
T1Dstatus              1       1.0   1.047    4.11 0.011  0.005 **
seqRun                 5       3.6   0.729    2.87 0.039  0.762   
Tri                    2       0.3   0.164    0.65 0.003  0.542   
Age                    1       0.7   0.739    2.90 0.008  0.398   
Parity                 1       0.6   0.623    2.45 0.007  0.936   
BMI                    1       0.5   0.497    1.95 0.005  0.431   
Age_Time_Interaction   1       0.1   0.145    0.57 0.002  0.461   
Residuals            339      86.3   0.254         0.913  0.118   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.1.4 Age at conception (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2       1.2   0.605    2.38 0.013  0.301  
T1Dstatus   1       1.0   1.047    4.12 0.011  0.011 *
seqRun      5       3.6   0.729    2.87 0.039  0.745  
Tri         2       0.3   0.164    0.65 0.003  0.523  
Parity      1       0.6   0.628    2.47 0.007  0.963  
BMI         1       0.5   0.501    1.97 0.005  0.559  
Age         1       0.7   0.730    2.87 0.008  0.238  
Residuals 340      86.4   0.254         0.914  0.111  
Total     353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.2 Body max index (BMI)

5.1.9.2.1 BMI interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2       1.2   0.605    2.38 0.013  0.283  
T1Dstatus              1       1.0   1.047    4.11 0.011  0.012 *
seqRun                 5       3.6   0.729    2.87 0.039  0.735  
Tri                    2       0.3   0.164    0.65 0.003  0.524  
Age                    1       0.7   0.739    2.90 0.008  0.421  
Parity                 1       0.6   0.623    2.45 0.007  0.927  
BMI                    1       0.5   0.497    1.95 0.005  0.441  
BMI_Time_Interaction   1       0.1   0.120    0.47 0.001  0.914  
Residuals            339      86.3   0.255         0.913  0.143  
Total                353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.2.2 BMI interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2       1.2   0.605    2.38 0.013  0.309  
T1Dstatus              1       1.0   1.047    4.11 0.011  0.012 *
seqRun                 5       3.6   0.729    2.87 0.039  0.745  
Tri                    2       0.3   0.164    0.65 0.003  0.562  
Age                    1       0.7   0.739    2.90 0.008  0.401  
Parity                 1       0.6   0.623    2.45 0.007  0.925  
BMI                    1       0.5   0.497    1.95 0.005  0.455  
BMI_Time_Interaction   1       0.1   0.140    0.55 0.001  0.740  
Residuals            339      86.3   0.255         0.913  0.131  
Total                353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.2.3 BMI (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.38 0.013  0.314   
T1Dstatus              1       1.0   1.047    4.11 0.011  0.008 **
seqRun                 5       3.6   0.729    2.87 0.039  0.723   
Tri                    2       0.3   0.164    0.65 0.003  0.577   
Age                    1       0.7   0.739    2.90 0.008  0.409   
Parity                 1       0.6   0.623    2.45 0.007  0.923   
BMI                    1       0.5   0.497    1.95 0.005  0.452   
BMI_Time_Interaction   1       0.2   0.169    0.66 0.002  0.346   
Residuals            339      86.2   0.254         0.913  0.105   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.2.4 BMI (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       1.2   0.605    2.38 0.013  0.297   
T1Dstatus   1       1.0   1.047    4.12 0.011  0.008 **
seqRun      5       3.6   0.729    2.87 0.039  0.750   
Tri         2       0.3   0.164    0.65 0.003  0.571   
Age         1       0.7   0.739    2.91 0.008  0.406   
Parity      1       0.6   0.623    2.45 0.007  0.937   
BMI         1       0.5   0.497    1.96 0.005  0.458   
Residuals 340      86.4   0.254         0.914  0.102   
Total     353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.3 HLA type

5.1.9.3.1 HLA type interaction with time (reference: DR34 )

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2       1.2   0.605    2.38 0.013  0.317  
T1Dstatus              1       1.0   1.047    4.12 0.011  0.013 *
Days                   1       0.2   0.248    0.98 0.003  0.370  
seqRun                 5       3.6   0.727    2.86 0.038  0.698  
Age                    1       0.7   0.735    2.89 0.008  0.401  
Parity                 1       0.6   0.625    2.46 0.007  0.923  
BMI                    1       0.5   0.496    1.95 0.005  0.519  
HLA_Time_Interaction   1       0.1   0.130    0.51 0.001  1.000  
Residuals            340      86.4   0.254         0.914  0.539  
Total                353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.3.2 HLA type interaction with time (reference: DRXX)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.38 0.013  0.301   
T1Dstatus              1       1.0   1.047    4.12 0.011  0.006 **
Days                   1       0.2   0.248    0.98 0.003  0.373   
seqRun                 5       3.6   0.727    2.86 0.038  0.718   
Age                    1       0.7   0.735    2.89 0.008  0.372   
Parity                 1       0.6   0.625    2.46 0.007  0.925   
BMI                    1       0.5   0.496    1.95 0.005  0.507   
HLA_Time_Interaction   1       0.1   0.139    0.55 0.001  1.000   
Residuals            340      86.4   0.254         0.914  0.330   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.3.3 HLA type interaction with time (reference: Group3o4)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.38 0.013  0.305   
T1Dstatus              1       1.0   1.047    4.12 0.011  0.009 **
Days                   1       0.2   0.248    0.98 0.003  0.406   
seqRun                 5       3.6   0.727    2.86 0.038  0.728   
Age                    1       0.7   0.735    2.89 0.008  0.352   
Parity                 1       0.6   0.625    2.46 0.007  0.918   
BMI                    1       0.5   0.496    1.95 0.005  0.500   
HLA_Time_Interaction   1       0.2   0.154    0.61 0.002  1.000   
Residuals            340      86.4   0.254         0.914  0.243   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.3.4 HLA type (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
Days        1       0.3   0.280    1.10 0.003  0.235  
seqRun      5       3.7   0.747    2.94 0.040  0.549  
Age         1       0.7   0.715    2.82 0.008  0.751  
Parity      1       0.7   0.665    2.62 0.007  0.676  
BMI         1       0.5   0.499    1.97 0.005  0.247  
T1Dstatus   1       1.0   0.984    3.88 0.010  0.018 *
HLA         2       1.1   0.560    2.21 0.012  0.407  
Residuals 341      86.5   0.254         0.915  0.089 .
Total     353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.4 Parity

5.1.9.4.1 Parity interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                         Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                       2       1.2   0.605    2.38 0.013   0.29   
T1Dstatus                 1       1.0   1.047    4.12 0.011   0.01 **
Days                      1       0.2   0.248    0.98 0.003   0.35   
seqRun                    5       3.6   0.727    2.86 0.038   0.72   
Age                       1       0.7   0.735    2.89 0.008   0.41   
Parity                    1       0.6   0.625    2.46 0.007   0.92   
BMI                       1       0.5   0.496    1.95 0.005   0.51   
Parity_Time_Interaction   1       0.1   0.105    0.41 0.001   0.91   
Residuals               340      86.4   0.254         0.914   0.10 . 
Total                   353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.4.2 Parity (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       1.2   0.605    2.39 0.013  0.282   
T1Dstatus   1       1.0   1.047    4.13 0.011  0.009 **
Days        1       0.2   0.248    0.98 0.003  0.360   
seqRun      5       3.6   0.727    2.87 0.038  0.694   
Age         1       0.7   0.735    2.90 0.008  0.365   
BMI         1       0.5   0.541    2.13 0.006  0.400   
Parity      1       0.6   0.580    2.29 0.006  0.949   
Residuals 341      86.5   0.254         0.915  0.084 . 
Total     353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.5 Mode of delivery

5.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.42 0.013  0.283   
T1Dstatus              1       1.0   1.047    4.18 0.011  0.007 **
MOD                    2       1.3   0.650    2.60 0.014  0.187   
Days                   1       0.2   0.247    0.99 0.003  0.380   
seqRun                 5       3.7   0.734    2.93 0.039  0.550   
Age                    1       0.8   0.838    3.35 0.009  0.015 * 
Parity                 1       0.6   0.625    2.50 0.007  0.863   
BMI                    1       0.5   0.544    2.18 0.006  0.146   
MOD_Time_Interaction   1       0.4   0.423    1.69 0.004  0.979   
Residuals            338      84.6   0.250         0.895  0.022 * 
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.42 0.013   0.28   
T1Dstatus              1       1.0   1.047    4.18 0.011   0.01 **
MOD                    2       1.3   0.650    2.60 0.014   0.18   
Days                   1       0.2   0.247    0.99 0.003   0.35   
seqRun                 5       3.7   0.734    2.93 0.039   0.60   
Age                    1       0.8   0.838    3.35 0.009   0.01 **
Parity                 1       0.6   0.625    2.50 0.007   0.87   
BMI                    1       0.5   0.544    2.18 0.006   0.11   
MOD_Time_Interaction   1       0.5   0.458    1.83 0.005   1.00   
Residuals            338      84.6   0.250         0.895   0.16   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.5.3 Mode of delivery interaction with time (reference: Labour)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.605    2.41 0.013  0.301   
T1Dstatus              1       1.0   1.047    4.17 0.011  0.006 **
MOD                    2       1.3   0.650    2.59 0.014  0.195   
Days                   1       0.2   0.247    0.99 0.003  0.355   
seqRun                 5       3.7   0.734    2.92 0.039  0.600   
Age                    1       0.8   0.838    3.34 0.009  0.014 * 
Parity                 1       0.6   0.625    2.49 0.007  0.873   
BMI                    1       0.5   0.544    2.17 0.006  0.126   
MOD_Time_Interaction   1       0.2   0.234    0.93 0.002  1.000   
Residuals            338      84.8   0.251         0.897  0.320   
Total                353      94.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.5.4 Mode of delivery (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
Days        1       0.3   0.280    1.12 0.003  0.254  
seqRun      5       3.7   0.747    2.98 0.040  0.558  
Age         1       0.7   0.715    2.85 0.008  0.765  
Parity      1       0.7   0.665    2.65 0.007  0.666  
BMI         1       0.5   0.499    1.99 0.005  0.262  
HLA         2       1.1   0.573    2.29 0.012  0.341  
T1Dstatus   1       1.0   0.956    3.81 0.010  0.014 *
MOD         2       1.5   0.742    2.96 0.016  0.054 .
Residuals 339      85.0   0.251         0.900  0.020 *
Total     353      94.5                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.6 Carbohydrate intake

5.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       1.3   0.632   2.510 0.015  0.223  
T1Dstatus               1       0.8   0.783   3.111 0.009  0.089 .
Carbs                   1       0.5   0.466   1.854 0.005  0.720  
seqRun                  5       3.5   0.707   2.808 0.041  0.981  
Tri                     2       0.3   0.153   0.609 0.004  0.414  
Age                     1       0.7   0.744   2.958 0.009  0.434  
Parity                  1       0.7   0.662   2.629 0.008  0.811  
BMI                     1       0.5   0.545   2.167 0.006  0.329  
Carb_Time_Interaction   1       0.3   0.272   1.080 0.003  0.186  
Residuals             310      78.0   0.252         0.901  0.486  
Total                 325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       1.3   0.632   2.508 0.015  0.241  
T1Dstatus               1       0.8   0.783   3.107 0.009  0.082 .
Carbs                   1       0.5   0.466   1.852 0.005  0.736  
seqRun                  5       3.5   0.707   2.806 0.041  0.964  
Tri                     2       0.3   0.153   0.609 0.004  0.404  
Age                     1       0.7   0.744   2.955 0.009  0.431  
Parity                  1       0.7   0.662   2.626 0.008  0.809  
BMI                     1       0.5   0.545   2.165 0.006  0.345  
Carb_Time_Interaction   1       0.2   0.195   0.774 0.002  0.757  
Residuals             310      78.1   0.252         0.902  0.581  
Total                 325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                     2       1.3   0.632   2.505 0.015   0.26
T1Dstatus               1       0.8   0.783   3.104 0.009   0.10
Carbs                   1       0.5   0.466   1.850 0.005   0.74
seqRun                  5       3.5   0.707   2.803 0.041   0.97
Tri                     2       0.3   0.153   0.608 0.004   0.41
Age                     1       0.7   0.744   2.952 0.009   0.44
Parity                  1       0.7   0.662   2.624 0.008   0.81
BMI                     1       0.5   0.545   2.162 0.006   0.35
Carb_Time_Interaction   1       0.1   0.115   0.457 0.001   1.00
Residuals             310      78.2   0.252         0.903   0.66
Total                 325      86.6                 1.000       
5.1.9.6.4 Carbohydrate (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      5       3.8   0.751   2.982 0.043  0.716  
Tri         2       0.3   0.154   0.611 0.004  0.415  
Age         1       0.7   0.741   2.945 0.009  0.628  
Parity      1       0.7   0.686   2.726 0.008  0.830  
BMI         1       0.5   0.535   2.126 0.006  0.192  
HLA         2       1.2   0.584   2.319 0.013  0.317  
T1Dstatus   1       0.8   0.761   3.023 0.009  0.079 .
Carbs       1       0.4   0.352   1.400 0.004  0.939  
Residuals 311      78.3   0.252         0.904  0.524  
Total     325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.7 Fibre intake

5.1.9.7.1 Fibre interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       1.3   0.632   2.515 0.015  0.255  
T1Dstatus                1       0.8   0.783   3.116 0.009  0.086 .
Fiber                    1       0.6   0.624   2.482 0.007  0.284  
seqRun                   5       3.6   0.717   2.854 0.041  0.938  
Tri                      2       0.3   0.152   0.607 0.004  0.425  
Age                      1       0.7   0.742   2.956 0.009  0.455  
Parity                   1       0.7   0.653   2.601 0.008  0.865  
BMI                      1       0.5   0.531   2.112 0.006  0.462  
Fiber_Time_Interaction   1       0.2   0.230   0.916 0.003  0.093 .
Residuals              310      77.9   0.251         0.899  0.289  
Total                  325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.7.2 Fibre interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       1.3   0.632   2.514 0.015  0.261  
T1Dstatus                1       0.8   0.783   3.114 0.009  0.092 .
Fiber                    1       0.6   0.624   2.481 0.007  0.276  
seqRun                   5       3.6   0.717   2.852 0.041  0.938  
Tri                      2       0.3   0.152   0.607 0.004  0.445  
Age                      1       0.7   0.742   2.954 0.009  0.438  
Parity                   1       0.7   0.653   2.599 0.008  0.854  
BMI                      1       0.5   0.531   2.111 0.006  0.481  
Fiber_Time_Interaction   1       0.2   0.188   0.750 0.002  0.994  
Residuals              310      77.9   0.251         0.900  0.485  
Total                  325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.7.3 Fibre interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                      2       1.3   0.632   2.513 0.015   0.21
T1Dstatus                1       0.8   0.783   3.113 0.009   0.10
Fiber                    1       0.6   0.624   2.480 0.007   0.29
seqRun                   5       3.6   0.717   2.851 0.041   0.93
Tri                      2       0.3   0.152   0.606 0.004   0.41
Age                      1       0.7   0.742   2.953 0.009   0.48
Parity                   1       0.7   0.653   2.598 0.008   0.86
BMI                      1       0.5   0.531   2.110 0.006   0.48
Fiber_Time_Interaction   1       0.2   0.161   0.639 0.002   1.00
Residuals              310      77.9   0.251         0.900   0.50
Total                  325      86.6                 1.000       
5.1.9.7.4 Fibre (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      5       3.8   0.751   2.989 0.043  0.710  
Tri         2       0.3   0.154   0.612 0.004  0.432  
Age         1       0.7   0.741   2.952 0.009  0.644  
Parity      1       0.7   0.686   2.733 0.008  0.803  
BMI         1       0.5   0.535   2.131 0.006  0.190  
HLA         2       1.2   0.584   2.324 0.013  0.312  
T1Dstatus   1       0.8   0.761   3.030 0.009  0.091 .
Fiber       1       0.5   0.534   2.127 0.006  0.444  
Residuals 311      78.1   0.251         0.902  0.337  
Total     325      86.6                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.8 1,5-AG (glucose control measurement)

5.1.9.8.1 1,5-AG interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       1.2   0.598    2.38 0.014  0.300   
T1Dstatus              1       1.2   1.163    4.62 0.013  0.005 **
Days                   1       0.2   0.246    0.98 0.003  0.233   
seqRun                 4       3.2   0.794    3.16 0.036  0.772   
Age                    1       0.8   0.800    3.18 0.009  0.233   
Parity                 1       0.6   0.580    2.31 0.007  0.894   
BMI                    1       0.4   0.446    1.77 0.005  0.282   
AG15                   1       0.8   0.832    3.31 0.010  0.006 **
AG15_T1D_Interaction   1       0.4   0.374    1.49 0.004  1.000   
Residuals            311      78.2   0.252         0.899  0.067 . 
Total                324      87.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.8.2 1,5-AG within T1D women

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       1.2   0.597   2.448 0.021   0.19   
Days        1       0.2   0.168   0.689 0.003   0.43   
seqRun      4       2.9   0.718   2.946 0.052   0.95   
Age         1       0.6   0.624   2.560 0.011   0.01 **
Parity      1       0.5   0.516   2.117 0.009   0.57   
BMI         1       0.5   0.540   2.214 0.010   0.12   
AG15        1       0.5   0.451   1.850 0.008   0.27   
Residuals 202      49.2   0.244         0.886   0.21   
Total     213      55.6                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
5.1.9.8.3 1,5-AG interaction with time (within non-T1D women)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      1.18   0.592    2.35 0.039   0.43
Days        1      0.26   0.260    1.03 0.009   0.22
seqRun      3      1.47   0.491    1.95 0.049   0.72
Age         1      0.67   0.668    2.65 0.022   0.63
Parity      1      0.49   0.487    1.93 0.016   0.53
BMI         1      0.26   0.255    1.01 0.008   0.86
AG15        1      0.74   0.741    2.94 0.024   0.26
Residuals 100     25.22   0.252         0.833   0.45
Total     110     30.29                 1.000       
5.1.9.8.4 1,5-AG (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       1.2   0.598    2.37 0.014  0.272   
T1Dstatus   1       1.2   1.163    4.62 0.013  0.002 **
Days        1       0.2   0.246    0.97 0.003  0.212   
seqRun      4       3.2   0.794    3.15 0.036  0.736   
Age         1       0.8   0.800    3.17 0.009  0.260   
Parity      1       0.6   0.580    2.30 0.007  0.899   
BMI         1       0.4   0.446    1.77 0.005  0.296   
AG15        1       0.8   0.832    3.30 0.010  0.004 **
Residuals 312      78.6   0.252         0.903  0.006 **
Total     324      87.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.1.9.9 Pre-eclampsia (within T1D women)


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

              Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA            2       1.2   0.620    2.55 0.020  0.196  
Days           1       0.2   0.162    0.66 0.003  0.485  
seqRun         4       3.1   0.778    3.20 0.051  0.879  
Age            1       0.6   0.644    2.65 0.011  0.016 *
Parity         1       0.6   0.566    2.33 0.009  0.608  
BMI            1       0.6   0.574    2.36 0.009  0.089 .
Preeclampsia   1       0.4   0.432    1.77 0.007  0.173  
Residuals    223      54.2   0.243         0.890  0.159  
Total        234      61.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

5.2 Differential abundance analysis Species taxonomic level

Differential abundance analysis with limma using voom pipeline with structural zeros - Gordon

Improved analysis using TMM normalization and voom with structural zeros.

A linear model is fit to the data and differential abundance is assessed using empirical bayes. The false discovery rate (FDR) for this analysis is set at 5%. For a OTU to be classified as differentially abundant (DA), its change in abundance between the groups (T1D vs nonT1D) must be significant. In the results tables to follow, the genes that are DE are those that have an adjusted p-value less than the FDR. Note that adjusted p-value is used opposed to the initial p-value as it has been adjusted for multiple testing. Therefore any adjusted p-value less than 0.05 is deemed statistically significant, identifying the associated gene as DA.

Those genes that are DA are then determined to be more- or less abundant depending on the direction of their log-fold change. Those OTUs with a positive log-fold change are more abundant, while those OTUs with a negative log-fold change are less abundant.

Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type

       nonT1D_vs_T1D  T1  T2  T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down               0   0   0   1        0        1        5         0         0         0
NotSig           336 347 338 330      349      348      343       349       349       349
Up                13   2  11  18        0        0        1         0         0         0
       noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down             0           0           4
NotSig         349         349         344
Up               0           0           1

Differentially abundant species were found between T1D and non-T1D women across pregnancy and within each trimester. No differentially abundant species were detected between trimesters in samples form T1D and non-T1D women together or separatelly.

Results for contrasts with significant differentially abundant species are shown below

Only those taxa with prevalence > 50% and LogFC > 0.5 of < -0.5 are considered as biologically relevant in our analyses.

5.2.1 Across all trimesters (T1D vs non-T1D)

  Classification LogFC   P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1    Bacteroides -1.54 0.00319    0.0695        0.507    58      1.65      70.2
                           Feature
1 4d7b30ba940df2f77a91e77e2836842c

From 11 OTUs that limma identified as differentially abundant, only one (further classified as Bacteroides caccae in blast), had >50% prevalence in either of the groups (i.e. T1D or non-T1D). Here, we will just show hoe to plot mean and standard error of this differentially abundant taxa, however, this code can be used to plot any taxa that was differentially abundant in the rest of the analysis.

5.2.2 Only Trimester 1 (nonT1D vs T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%     
<0 rows> (or 0-length row.names)

5.2.3 Only Trimester 2 (nonT1D vs T1D)

   Classification LogFC   P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Lachnospiraceae  1.46 0.00273    0.0734        0.311  70.5     0.153        44

5.2.4 Only Trimester 3 (nonT1D vs T1D)

  Classification LogFC    P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1    Bacteroides -1.97 0.000658    0.0164        0.419  58.7      2.08      77.6

5.2.5 T1 vs T2 (T1D and non-T1D data)

 [1] Classification LogFC          P.Val          adj.P.Val      T1:mean%      
 [6] T1Prev%        T2:mean%       T2Prev%        T3:mean%       T3Prev%       
<0 rows> (or 0-length row.names)

5.2.6 T2 vs T3 (T1D and non-T1D data)

  Classification  LogFC    P.Val adj.P.Val mean% Prev%
1  Oscillibacter -0.579 9.68e-05    0.0338 0.064  53.6
2  Oscillibacter -0.579 9.68e-05    0.0338 0.050  43.0
3  Oscillibacter -0.579 9.68e-05    0.0338 0.085  55.7

5.2.7 T1 vs T3 (T1D and non-T1D data)

       Classification  LogFC    P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1 Erysipelotrichaceae -0.753 0.002511    0.0674    0.133    66.1     0.18    72.8
2       Streptococcus -0.998 0.000107    0.0125    0.149    51.8     0.25    57.6
3       Oscillibacter -0.734 0.000512    0.0298    0.064    53.6     0.05    43.0
  T3:mean% T3Prev%
1    0.229    82.1
2    0.326    71.4
3    0.085    55.7

5.2.8 T1 vs T2 (in women with T1D)

   Classification LogFC    P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1 Lachnospiraceae -1.09 0.000426    0.0744    0.057    31.6    0.206    54.2

5.2.9 T2 vs T3 (in women with T1D)

[1] "No DA taxa"

5.2.10 T1 vs T3 (in women with T1D)

[1] "No DA taxa"

5.2.11 T1 vs T2 (in women without T1D)

[1] "No DA taxa"

5.2.12 T2 vs T3 (in women without T1D)

[1] "No DA taxa"

5.2.13 T1 vs T3 (in women without T1D)

  Classification LogFC    P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
1  Oscillibacter -1.37 8.07e-05   0.00939    0.024    38.9     0.11      62

6 Genus taxonomic level

6.1 Microbial community composition analysis at Genus level (Beta diversity analysis)

6.1.1 Interaction between T1D status and Time


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun                 5       1.9   0.389    2.90 0.039  0.548  
Days                   1       0.2   0.233    1.74 0.005  0.085 .
T1D_Time_Interaction   1       1.0   1.032    7.69 0.021  0.051 .
Age                    1       0.4   0.356    2.65 0.007  0.826  
Parity                 1       0.3   0.335    2.49 0.007  0.497  
BMI                    1       0.1   0.089    0.67 0.002  0.873  
HLA                    2       0.5   0.237    1.77 0.009  0.599  
T1Dstatus              1       0.1   0.096    0.72 0.002  0.964  
Residuals            340      45.6   0.134         0.909  0.757  
Total                353      50.2                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.051

6.1.2 T1D status in trimester 1


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

               Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
SeqRun          3      0.36  0.1184   0.802 0.044   0.72
Nulliparous     1      0.12  0.1167   0.791 0.015   0.59
Age_LMP         1      0.22  0.2165   1.467 0.027   0.15
BMI_conception  1      0.06  0.0632   0.428 0.008   0.90
HLA.6DRML       2      0.26  0.1307   0.885 0.033   0.56
T1Dstatus       1      0.18  0.1777   1.203 0.022   0.27
Residuals      46      6.79  0.1477         0.851       
Total          55      7.98                 1.000       
[1] 0.274

Beta diversity Plot

6.1.3 T1D status in trimester 2


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
SeqRun           4      0.74   0.184    1.34 0.041  0.165   
Nulliparous      1      0.20   0.205    1.48 0.011  0.153   
Age_LMP          1      0.19   0.191    1.39 0.011  0.213   
BMI_conception   1      0.07   0.066    0.48 0.004  0.877   
HLA.6DRML        2      0.20   0.099    0.72 0.011  0.756   
T1Dstatus        1      0.49   0.487    3.53 0.027  0.004 **
Residuals      117     16.13   0.138         0.895          
Total          127     18.01                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.004

Beta diversity Plot

6.1.4 T1D status in trimester 3


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
SeqRun           5      0.90   0.180    1.32 0.049  0.164   
Nulliparous      1      0.22   0.220    1.62 0.012  0.113   
Age_LMP          1      0.17   0.173    1.28 0.010  0.241   
BMI_conception   1      0.10   0.100    0.74 0.006  0.600   
HLA.6DRML        2      0.16   0.078    0.57 0.009  0.875   
T1Dstatus        1      0.47   0.470    3.46 0.026  0.005 **
Residuals      119     16.19   0.136         0.889          
Total          130     18.20                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.005

Beta diversity Plot

6.1.5 Days within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.68   0.338    2.95 0.023   0.19
seqRun      4      1.92   0.481    4.20 0.066   0.81
Age         1      0.29   0.290    2.54 0.010   0.31
Parity      1      0.24   0.241    2.11 0.008   0.72
BMI         1      0.24   0.236    2.06 0.008   0.20
Days        1      0.12   0.117    1.02 0.004   0.12
Residuals 224     25.65   0.115         0.880   0.27
Total     234     29.14                 1.000       

Beta diversity Plot

6.1.6 Trimester within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.68   0.338    2.94 0.023   0.17
seqRun      4      1.92   0.481    4.19 0.066   0.80
Age         1      0.29   0.290    2.53 0.010   0.28
Parity      1      0.24   0.241    2.10 0.008   0.73
BMI         1      0.24   0.236    2.06 0.008   0.18
Tri         2      0.15   0.076    0.66 0.005   0.35
Residuals 223     25.62   0.115         0.879   0.31
Total     234     29.14                 1.000       

Beta diversity Plot

6.1.7 Days within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.67   0.333    2.03 0.033  0.490  
seqRun      5      0.72   0.144    0.88 0.036  0.946  
Age         1      0.55   0.550    3.36 0.027  0.308  
Parity      1      0.38   0.384    2.34 0.019  0.058 .
BMI         1      0.12   0.124    0.76 0.006  0.596  
Days        1      0.17   0.165    1.01 0.008  0.121  
Residuals 107     17.51   0.164         0.870  0.661  
Total     118     20.12                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

6.1.8 Trimester within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.67   0.333    2.01 0.033  0.490  
seqRun      5      0.72   0.144    0.87 0.036  0.955  
Age         1      0.55   0.550    3.32 0.027  0.274  
Parity      1      0.38   0.384    2.32 0.019  0.082 .
BMI         1      0.12   0.124    0.75 0.006  0.590  
Tri         2      0.14   0.068    0.41 0.007  0.852  
Residuals 106     17.54   0.165         0.872  0.808  
Total     118     20.12                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

6.1.9 Other factors

6.1.9.1 Age at conception

6.1.9.1.1 Age at conception interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.61 0.009  0.705   
T1Dstatus              1       1.1   1.106    8.22 0.022  0.005 **
seqRun                 5       1.9   0.383    2.85 0.038  0.649   
Tri                    2       0.2   0.085    0.64 0.003  0.515   
Age                    1       0.4   0.410    3.05 0.008  0.903   
Parity                 1       0.3   0.309    2.30 0.006  0.974   
BMI                    1       0.1   0.103    0.77 0.002  0.820   
Age_Time_Interaction   1       0.1   0.143    1.06 0.003  0.681   
Residuals            339      45.6   0.134         0.909  0.294   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.1.2 Age at conception interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.60 0.009  0.733   
T1Dstatus              1       1.1   1.106    8.21 0.022  0.005 **
seqRun                 5       1.9   0.383    2.84 0.038  0.654   
Tri                    2       0.2   0.085    0.63 0.003  0.525   
Age                    1       0.4   0.410    3.04 0.008  0.882   
Parity                 1       0.3   0.309    2.29 0.006  0.974   
BMI                    1       0.1   0.103    0.77 0.002  0.830   
Age_Time_Interaction   1       0.0   0.043    0.32 0.001  0.854   
Residuals            339      45.7   0.135         0.911  0.303   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.1.3 Age at conception interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.61 0.009  0.742   
T1Dstatus              1       1.1   1.106    8.21 0.022  0.005 **
seqRun                 5       1.9   0.383    2.84 0.038  0.633   
Tri                    2       0.2   0.085    0.63 0.003  0.515   
Age                    1       0.4   0.410    3.04 0.008  0.886   
Parity                 1       0.3   0.309    2.29 0.006  0.974   
BMI                    1       0.1   0.103    0.77 0.002  0.841   
Age_Time_Interaction   1       0.1   0.060    0.44 0.001  0.553   
Residuals            339      45.7   0.135         0.910  0.249   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.1.4 Age at conception (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.4   0.216    1.61 0.009  0.718   
T1Dstatus   1       1.1   1.106    8.22 0.022  0.007 **
seqRun      5       1.9   0.383    2.85 0.038  0.645   
Tri         2       0.2   0.085    0.64 0.003  0.520   
Parity      1       0.3   0.303    2.25 0.006  0.994   
BMI         1       0.1   0.103    0.76 0.002  0.865   
Age         1       0.4   0.416    3.09 0.008  0.746   
Residuals 340      45.7   0.135         0.911  0.241   
Total     353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.2 Body max index (BMI)

6.1.9.2.1 BMI interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.60 0.009  0.738   
T1Dstatus              1       1.1   1.106    8.20 0.022  0.002 **
seqRun                 5       1.9   0.383    2.84 0.038  0.652   
Tri                    2       0.2   0.085    0.63 0.003  0.526   
Age                    1       0.4   0.410    3.04 0.008  0.902   
Parity                 1       0.3   0.309    2.29 0.006  0.974   
BMI                    1       0.1   0.103    0.77 0.002  0.826   
BMI_Time_Interaction   1       0.0   0.019    0.14 0.000  0.987   
Residuals            339      45.7   0.135         0.911  0.338   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.2.2 BMI interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.60 0.009  0.743   
T1Dstatus              1       1.1   1.106    8.20 0.022  0.004 **
seqRun                 5       1.9   0.383    2.84 0.038  0.645   
Tri                    2       0.2   0.085    0.63 0.003  0.482   
Age                    1       0.4   0.410    3.04 0.008  0.897   
Parity                 1       0.3   0.309    2.29 0.006  0.969   
BMI                    1       0.1   0.103    0.77 0.002  0.814   
BMI_Time_Interaction   1       0.0   0.023    0.17 0.000  0.974   
Residuals            339      45.7   0.135         0.911  0.336   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.2.3 BMI (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.60 0.009  0.739   
T1Dstatus              1       1.1   1.106    8.21 0.022  0.007 **
seqRun                 5       1.9   0.383    2.84 0.038  0.637   
Tri                    2       0.2   0.085    0.63 0.003  0.536   
Age                    1       0.4   0.410    3.04 0.008  0.887   
Parity                 1       0.3   0.309    2.29 0.006  0.972   
BMI                    1       0.1   0.103    0.77 0.002  0.797   
BMI_Time_Interaction   1       0.0   0.047    0.35 0.001  0.822   
Residuals            339      45.7   0.135         0.910  0.312   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.2.4 BMI (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.4   0.216    1.61 0.009  0.716   
T1Dstatus   1       1.1   1.106    8.22 0.022  0.004 **
seqRun      5       1.9   0.383    2.85 0.038  0.614   
Tri         2       0.2   0.085    0.64 0.003  0.577   
Age         1       0.4   0.410    3.05 0.008  0.881   
Parity      1       0.3   0.309    2.30 0.006  0.975   
BMI         1       0.1   0.103    0.77 0.002  0.802   
Residuals 340      45.7   0.135         0.911  0.259   
Total     353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.3 HLA type

6.1.9.3.1 HLA type interaction with time (reference: DR34 )

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.61 0.009  0.726   
T1Dstatus              1       1.1   1.106    8.25 0.022  0.002 **
Days                   1       0.3   0.258    1.92 0.005  0.161   
seqRun                 5       1.9   0.376    2.80 0.037  0.647   
Age                    1       0.4   0.387    2.88 0.008  0.905   
Parity                 1       0.3   0.304    2.26 0.006  0.978   
BMI                    1       0.1   0.101    0.76 0.002  0.826   
HLA_Time_Interaction   1       0.1   0.106    0.79 0.002  0.996   
Residuals            340      45.6   0.134         0.909  0.233   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.3.2 HLA type interaction with time (reference: DRXX)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.61 0.009  0.719   
T1Dstatus              1       1.1   1.106    8.24 0.022  0.002 **
Days                   1       0.3   0.258    1.92 0.005  0.160   
seqRun                 5       1.9   0.376    2.80 0.037  0.629   
Age                    1       0.4   0.387    2.88 0.008  0.906   
Parity                 1       0.3   0.304    2.26 0.006  0.975   
BMI                    1       0.1   0.101    0.76 0.002  0.822   
HLA_Time_Interaction   1       0.1   0.052    0.39 0.001  1.000   
Residuals            340      45.7   0.134         0.910  0.287   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.3.3 HLA type interaction with time (reference: Group3o4)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.61 0.009  0.723   
T1Dstatus              1       1.1   1.106    8.24 0.022  0.004 **
Days                   1       0.3   0.258    1.92 0.005  0.171   
seqRun                 5       1.9   0.376    2.80 0.037  0.652   
Age                    1       0.4   0.387    2.88 0.008  0.902   
Parity                 1       0.3   0.304    2.26 0.006  0.969   
BMI                    1       0.1   0.101    0.76 0.002  0.814   
HLA_Time_Interaction   1       0.1   0.064    0.48 0.001  0.996   
Residuals            340      45.6   0.134         0.910  0.248   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.3.4 HLA type (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
Days        1       0.3   0.276    2.06 0.006  0.126  
seqRun      5       1.9   0.381    2.84 0.038  0.591  
Age         1       0.5   0.450    3.36 0.009  0.631  
Parity      1       0.4   0.383    2.86 0.008  0.174  
BMI         1       0.1   0.113    0.84 0.002  0.663  
T1Dstatus   1       0.9   0.853    6.37 0.017  0.016 *
HLA         2       0.5   0.245    1.83 0.010  0.567  
Residuals 341      45.7   0.134         0.911  0.175  
Total     353      50.2                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.4 Parity

6.1.9.4.1 Parity interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                         Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                       2       0.4   0.216    1.61 0.009  0.713   
T1Dstatus                 1       1.1   1.106    8.24 0.022  0.002 **
Days                      1       0.3   0.258    1.92 0.005  0.172   
seqRun                    5       1.9   0.376    2.80 0.037  0.646   
Age                       1       0.4   0.387    2.88 0.008  0.881   
Parity                    1       0.3   0.304    2.26 0.006  0.971   
BMI                       1       0.1   0.101    0.76 0.002  0.835   
Parity_Time_Interaction   1       0.1   0.075    0.56 0.001  0.494   
Residuals               340      45.6   0.134         0.909  0.197   
Total                   353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.4.2 Parity (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.4   0.216    1.61 0.009  0.691   
T1Dstatus   1       1.1   1.106    8.25 0.022  0.004 **
Days        1       0.3   0.258    1.92 0.005  0.180   
seqRun      5       1.9   0.376    2.81 0.037  0.656   
Age         1       0.4   0.387    2.89 0.008  0.894   
BMI         1       0.1   0.120    0.89 0.002  0.535   
Parity      1       0.3   0.285    2.13 0.006  0.989   
Residuals 341      45.7   0.134         0.911  0.179   
Total     353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.5 Mode of delivery

6.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.64 0.009  0.759   
T1Dstatus              1       1.1   1.106    8.37 0.022  0.002 **
MOD                    2       0.8   0.413    3.13 0.016  0.137   
Days                   1       0.3   0.251    1.90 0.005  0.174   
seqRun                 5       1.9   0.384    2.91 0.038  0.592   
Age                    1       0.5   0.535    4.05 0.011  0.117   
Parity                 1       0.3   0.317    2.40 0.006  0.883   
BMI                    1       0.1   0.071    0.54 0.001  0.987   
MOD_Time_Interaction   1       0.1   0.073    0.55 0.001  1.000   
Residuals            338      44.6   0.132         0.890  0.088 . 
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.64 0.009  0.721   
T1Dstatus              1       1.1   1.106    8.39 0.022  0.003 **
MOD                    2       0.8   0.413    3.13 0.016  0.141   
Days                   1       0.3   0.251    1.90 0.005  0.184   
seqRun                 5       1.9   0.384    2.92 0.038  0.586   
Age                    1       0.5   0.535    4.06 0.011  0.105   
Parity                 1       0.3   0.317    2.41 0.006  0.882   
BMI                    1       0.1   0.071    0.54 0.001  0.991   
MOD_Time_Interaction   1       0.2   0.188    1.42 0.004  1.000   
Residuals            338      44.5   0.132         0.887  0.447   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.5.3 Mode of delivery interaction with time (reference: Labour)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.216    1.64 0.009  0.732   
T1Dstatus              1       1.1   1.106    8.38 0.022  0.003 **
MOD                    2       0.8   0.413    3.13 0.016  0.162   
Days                   1       0.3   0.251    1.90 0.005  0.179   
seqRun                 5       1.9   0.384    2.91 0.038  0.613   
Age                    1       0.5   0.535    4.05 0.011  0.111   
Parity                 1       0.3   0.317    2.40 0.006  0.897   
BMI                    1       0.1   0.071    0.54 0.001  0.990   
MOD_Time_Interaction   1       0.1   0.108    0.82 0.002  1.000   
Residuals            338      44.6   0.132         0.889  0.395   
Total                353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.5.4 Mode of delivery (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
Days        1       0.3   0.276    2.09 0.006  0.146   
seqRun      5       1.9   0.381    2.88 0.038  0.584   
Age         1       0.5   0.450    3.41 0.009  0.609   
Parity      1       0.4   0.383    2.90 0.008  0.198   
BMI         1       0.1   0.113    0.85 0.002  0.677   
HLA         2       0.4   0.184    1.39 0.007  0.838   
T1Dstatus   1       1.0   0.977    7.40 0.019  0.006 **
MOD         2       1.0   0.496    3.76 0.020  0.061 . 
Residuals 339      44.7   0.132         0.891  0.062 . 
Total     353      50.2                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.6 Carbohydrate intake

6.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2       0.5   0.254    1.96 0.011  0.576   
T1Dstatus               1       0.7   0.660    5.09 0.015  0.037 * 
Carbs                   1       0.2   0.204    1.57 0.005  0.689   
seqRun                  5       2.2   0.431    3.32 0.048  0.714   
Tri                     2       0.2   0.075    0.58 0.003  0.499   
Age                     1       0.4   0.414    3.19 0.009  0.811   
Parity                  1       0.3   0.325    2.51 0.007  0.946   
BMI                     1       0.1   0.128    0.98 0.003  0.715   
Carb_Time_Interaction   1       0.3   0.260    2.00 0.006  0.002 **
Residuals             310      40.2   0.130         0.893  0.553   
Total                 325      45.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       0.5   0.254    1.96 0.011  0.562  
T1Dstatus               1       0.7   0.660    5.08 0.015  0.041 *
Carbs                   1       0.2   0.204    1.57 0.005  0.650  
seqRun                  5       2.2   0.431    3.31 0.048  0.695  
Tri                     2       0.2   0.075    0.58 0.003  0.484  
Age                     1       0.4   0.414    3.18 0.009  0.813  
Parity                  1       0.3   0.325    2.50 0.007  0.949  
BMI                     1       0.1   0.128    0.98 0.003  0.744  
Carb_Time_Interaction   1       0.2   0.152    1.17 0.003  0.083 .
Residuals             310      40.3   0.130         0.896  0.604  
Total                 325      45.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       0.5   0.254    1.95 0.011  0.584  
T1Dstatus               1       0.7   0.660    5.08 0.015  0.049 *
Carbs                   1       0.2   0.204    1.56 0.005  0.678  
seqRun                  5       2.2   0.431    3.31 0.048  0.699  
Tri                     2       0.2   0.075    0.58 0.003  0.495  
Age                     1       0.4   0.414    3.18 0.009  0.826  
Parity                  1       0.3   0.325    2.50 0.007  0.952  
BMI                     1       0.1   0.128    0.98 0.003  0.765  
Carb_Time_Interaction   1       0.1   0.128    0.98 0.003  0.048 *
Residuals             310      40.3   0.130         0.896  0.615  
Total                 325      45.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.6.4 Carbohydrate (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3      0.45   0.150   1.092 0.065  0.001 ***
Age        1      0.34   0.336   2.446 0.048  0.001 ***
Parity     1      0.09   0.094   0.686 0.014  0.001 ***
BMI        1      0.09   0.094   0.685 0.014  0.001 ***
HLA        2      0.27   0.134   0.979 0.039  0.440    
T1Dstatus  1      0.17   0.171   1.243 0.025  0.263    
Carbs      1      0.17   0.166   1.208 0.024  0.292    
Residuals 39      5.35   0.137         0.772  0.331    
Total     49      6.93                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.6.5 Carbohydrate (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun      4      1.20   0.300   2.325 0.062   0.30
Age         1      0.22   0.217   1.683 0.011   0.90
Parity      1      0.22   0.218   1.690 0.011   0.71
BMI         1      0.04   0.038   0.294 0.002   0.76
HLA         2      0.24   0.118   0.914 0.012   0.80
T1Dstatus   1      0.27   0.271   2.097 0.014   0.12
Carbs       1      0.13   0.131   1.015 0.007   0.57
Residuals 132     17.06   0.129         0.881   0.53
Total     143     19.38                 1.000       
6.1.9.6.6 Carbohydrate (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      4      0.95  0.2373   1.727 0.051  0.776  
Age         1      0.15  0.1497   1.089 0.008  0.184  
Parity      1      0.25  0.2508   1.825 0.014  0.614  
BMI         1      0.09  0.0945   0.687 0.005  0.140  
HLA         2      0.17  0.0869   0.633 0.009  0.915  
T1Dstatus   1      0.30  0.3024   2.200 0.016  0.097 .
Carbs       1      0.14  0.1418   1.032 0.008  0.473  
Residuals 120     16.49  0.1374         0.889  0.747  
Total     131     18.55                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.7 Fibre intake

6.1.9.7.1 Fibre interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
HLA                      2       0.5   0.254    1.97 0.011  0.564    
T1Dstatus                1       0.7   0.660    5.12 0.015  0.046 *  
Fiber                    1       0.3   0.297    2.30 0.007  0.365    
seqRun                   5       2.3   0.458    3.55 0.051  0.553    
Tri                      2       0.1   0.072    0.56 0.003  0.535    
Age                      1       0.4   0.410    3.18 0.009  0.801    
Parity                   1       0.3   0.308    2.39 0.007  0.983    
BMI                      1       0.1   0.119    0.92 0.003  0.839    
Fiber_Time_Interaction   1       0.3   0.272    2.11 0.006  0.001 ***
Residuals              310      40.0   0.129         0.889  0.306    
Total                  325      45.0                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.7.2 Fibre interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       0.5   0.254    1.96 0.011  0.601  
T1Dstatus                1       0.7   0.660    5.10 0.015  0.036 *
Fiber                    1       0.3   0.297    2.29 0.007  0.379  
seqRun                   5       2.3   0.458    3.53 0.051  0.569  
Tri                      2       0.1   0.072    0.56 0.003  0.506  
Age                      1       0.4   0.410    3.16 0.009  0.823  
Parity                   1       0.3   0.308    2.38 0.007  0.976  
BMI                      1       0.1   0.119    0.92 0.003  0.827  
Fiber_Time_Interaction   1       0.1   0.105    0.81 0.002  0.765  
Residuals              310      40.2   0.130         0.892  0.532  
Total                  325      45.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.7.3 Fibre interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       0.5   0.254    1.97 0.011  0.589  
T1Dstatus                1       0.7   0.660    5.11 0.015  0.039 *
Fiber                    1       0.3   0.297    2.30 0.007  0.386  
seqRun                   5       2.3   0.458    3.54 0.051  0.560  
Tri                      2       0.1   0.072    0.56 0.003  0.524  
Age                      1       0.4   0.410    3.17 0.009  0.825  
Parity                   1       0.3   0.308    2.39 0.007  0.978  
BMI                      1       0.1   0.119    0.92 0.003  0.834  
Fiber_Time_Interaction   1       0.2   0.202    1.56 0.004  0.606  
Residuals              310      40.1   0.129         0.890  0.540  
Total                  325      45.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.7.4 Fibre (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3      0.45   0.150   1.077 0.065  0.001 ***
Age        1      0.34   0.336   2.414 0.048  0.001 ***
Parity     1      0.09   0.094   0.677 0.014  0.001 ***
BMI        1      0.09   0.094   0.676 0.014  0.001 ***
HLA        2      0.27   0.134   0.966 0.039  0.435    
T1Dstatus  1      0.17   0.171   1.227 0.025  0.266    
Fiber      1      0.09   0.094   0.673 0.014  0.658    
Residuals 39      5.43   0.139         0.783  0.514    
Total     49      6.93                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.7.5 Fibre (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun      4      1.20   0.300   2.324 0.062   0.31
Age         1      0.22   0.217   1.683 0.011   0.88
Parity      1      0.22   0.218   1.690 0.011   0.69
BMI         1      0.04   0.038   0.294 0.002   0.75
HLA         2      0.24   0.118   0.914 0.012   0.78
T1Dstatus   1      0.27   0.271   2.097 0.014   0.13
Fiber       1      0.13   0.128   0.989 0.007   0.59
Residuals 132     17.06   0.129         0.881   0.57
Total     143     19.38                 1.000       
6.1.9.7.6 Fibre (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      4      0.95   0.237    1.76 0.051  0.775  
Age         1      0.15   0.150    1.11 0.008  0.145  
Parity      1      0.25   0.251    1.86 0.014  0.647  
BMI         1      0.09   0.094    0.70 0.005  0.118  
HLA         2      0.17   0.087    0.65 0.009  0.913  
T1Dstatus   1      0.30   0.302    2.24 0.016  0.085 .
Fiber       1      0.47   0.467    3.47 0.025  0.019 *
Residuals 120     16.17   0.135         0.871  0.553  
Total     131     18.55                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.8 1,5-AG (glucose control measurement)

6.1.9.8.1 1,5-AG interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.5   0.235    1.78 0.010  0.644   
T1Dstatus              1       1.3   1.253    9.49 0.027  0.003 **
Days                   1       0.3   0.259    1.96 0.006  0.069 . 
seqRun                 4       1.8   0.444    3.36 0.038  0.214   
Age                    1       0.5   0.518    3.92 0.011  0.854   
Parity                 1       0.3   0.259    1.96 0.006  0.995   
BMI                    1       0.1   0.110    0.84 0.002  0.153   
AG15                   1       0.5   0.501    3.79 0.011  0.086 . 
AG15_T1D_Interaction   1       0.2   0.221    1.67 0.005  1.000   
Residuals            311      41.1   0.132         0.884  0.041 * 
Total                324      46.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.8.2 1,5-AG within T1D women

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.75   0.375    3.31 0.029  0.083 .
Days        1      0.17   0.171    1.51 0.007  0.069 .
seqRun      4      1.60   0.400    3.53 0.061  0.943  
Age         1      0.27   0.270    2.38 0.010  0.382  
Parity      1      0.19   0.185    1.63 0.007  0.627  
BMI         1      0.21   0.207    1.82 0.008  0.125  
AG15        1      0.19   0.194    1.71 0.007  0.848  
Residuals 202     22.91   0.113         0.871  0.232  
Total     213     26.28                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
6.1.9.8.3 1,5-AG interaction with time (within non-T1D women)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.71   0.355    2.23 0.037   0.48
Days        1      0.21   0.212    1.33 0.011   0.15
seqRun      3      0.57   0.189    1.19 0.030   0.83
Age         1      0.65   0.648    4.07 0.034   0.45
Parity      1      0.39   0.387    2.43 0.020   0.11
BMI         1      0.12   0.123    0.77 0.006   0.78
AG15        1      0.56   0.560    3.52 0.029   0.10
Residuals 100     15.92   0.159         0.832   0.31
Total     110     19.13                 1.000       
6.1.9.8.4 1,5-AG (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.5   0.235    1.77 0.010  0.669   
T1Dstatus   1       1.3   1.253    9.47 0.027  0.002 **
Days        1       0.3   0.259    1.96 0.006  0.079 . 
seqRun      4       1.8   0.444    3.35 0.038  0.212   
Age         1       0.5   0.518    3.91 0.011  0.851   
Parity      1       0.3   0.259    1.96 0.006  0.995   
BMI         1       0.1   0.110    0.83 0.002  0.182   
AG15        1       0.5   0.501    3.78 0.011  0.091 . 
Residuals 312      41.3   0.132         0.889  0.011 * 
Total     324      46.5                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

6.1.9.9 Pre-eclampsia (within T1D women)


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

              Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA            2      0.68   0.338    2.95 0.023   0.18
Days           1      0.16   0.156    1.36 0.005   0.16
seqRun         4      1.89   0.471    4.12 0.065   0.81
Age            1      0.27   0.274    2.39 0.009   0.47
Parity         1      0.24   0.244    2.13 0.008   0.65
BMI            1      0.25   0.249    2.17 0.009   0.11
Preeclampsia   1      0.13   0.133    1.16 0.005   0.26
Residuals    223     25.52   0.114         0.876   0.25
Total        234     29.14                 1.000       

6.2 Differential abundance analysis Genus taxonomic level

Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type

       nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down               0  0  0  0        0        1        1         0         0         0
NotSig            50 50 50 51       52       51       51        52        52        52
Up                 2  2  2  1        0        0        0         0         0         0
       noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down             0           0           1
NotSig          52          52          51
Up               0           0           0

Results for contrasts with significant differentially abundant strains shown below

6.2.1 Across all trimesters (T1D vs non-T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%      Feature       
<0 rows> (or 0-length row.names)

6.2.2 Only Trimester 1 (nonT1D vs T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%     
<0 rows> (or 0-length row.names)

6.2.3 Only Trimester 2 (nonT1D vs T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%     
<0 rows> (or 0-length row.names)

6.2.4 Only Trimester 3 (nonT1D vs T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%     
<0 rows> (or 0-length row.names)

6.2.5 T1 vs T2 (T1D and non-T1D data)

[1] "No DA taxa"

6.2.6 T2 vs T3 (T1D and non-T1D data)

  Classification  LogFC    P.Val adj.P.Val mean% Prev%
1  Oscillibacter -0.531 0.000484    0.0252 0.077  50.0
2  Oscillibacter -0.531 0.000484    0.0252 0.070  42.4
3  Oscillibacter -0.531 0.000484    0.0252 0.115  55.7

Nothing left after filtering by prevalence and LogFC

6.2.7 T1 vs T3 (T1D and non-T1D data)

  Classification  LogFC    P.Val adj.P.Val mean% Prev%
1  Oscillibacter -0.815 0.000186   0.00968 0.077  50.0
2  Oscillibacter -0.815 0.000186   0.00968 0.070  42.4
3  Oscillibacter -0.815 0.000186   0.00968 0.115  55.7

6.2.8 T1 vs T2 (in women with T1D)

[1] "No DA taxa"

6.2.9 T2 vs T3 (in women with T1D)

[1] "No DA taxa"

6.2.10 T1 vs T3 (in women with T1D)

[1] "No DA taxa"

6.2.11 T1 vs T2 (in women without T1D)

[1] "No DA taxa"

6.2.12 T2 vs T3 (in women without T1D)

[1] "No DA taxa"

6.2.13 T1 vs T3 (in women without T1D)

  Classification LogFC    P.Val adj.P.Val mean% Prev%
1  Oscillibacter -1.26 0.000439    0.0228 0.028  33.3
2  Oscillibacter -1.26 0.000439    0.0228 0.156  60.0

7 Family taxonomic level

7.1 Microbial community composition analysis at Family level (Beta diversity analysis)

7.1.1 Interaction between T1D status and Time


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun                 5       1.8   0.360    3.32 0.044  0.566  
Days                   1       0.2   0.224    2.07 0.005  0.040 *
T1D_Time_Interaction   1       1.0   0.999    9.22 0.024  0.043 *
Age                    1       0.3   0.266    2.46 0.006  0.742  
Parity                 1       0.2   0.172    1.59 0.004  0.999  
BMI                    1       0.2   0.226    2.08 0.006  0.415  
HLA                    2       0.4   0.194    1.79 0.009  0.567  
T1Dstatus              1       0.1   0.060    0.55 0.001  0.966  
Residuals            340      36.9   0.108         0.899  0.761  
Total                353      41.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.043

7.1.2 T1D status in trimester 1


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

               Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
SeqRun          3      0.34   0.115   1.080 0.057   0.38
Nulliparous     1      0.13   0.132   1.248 0.022   0.28
Age_LMP         1      0.15   0.152   1.430 0.025   0.19
BMI_conception  1      0.09   0.086   0.812 0.014   0.56
HLA.6DRML       2      0.25   0.125   1.176 0.042   0.31
T1Dstatus       1      0.16   0.156   1.473 0.026   0.21
Residuals      46      4.87   0.106         0.813       
Total          55      5.99                 1.000       
[1] 0.212

Beta diversity Plot

7.1.3 T1D status in trimester 2


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
SeqRun           4      0.58   0.145    1.26 0.038  0.212   
Nulliparous      1      0.08   0.082    0.72 0.005  0.607   
Age_LMP          1      0.18   0.178    1.55 0.012  0.139   
BMI_conception   1      0.19   0.193    1.68 0.013  0.118   
HLA.6DRML        2      0.20   0.098    0.86 0.013  0.592   
T1Dstatus        1      0.46   0.456    3.97 0.030  0.004 **
Residuals      117     13.42   0.115         0.889          
Total          127     15.10                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.004

Beta diversity Plot

7.1.4 T1D status in trimester 3


Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception +      HLA.6DRML + T1Dstatus, data = Meta_dfTri) 

Permutation: free
Number of permutations: 999

Terms added sequentially (first to last)

                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
SeqRun           5      0.88   0.175    1.59 0.058  0.081 . 
Nulliparous      1      0.19   0.187    1.70 0.012  0.133   
Age_LMP          1      0.17   0.165    1.50 0.011  0.182   
BMI_conception   1      0.17   0.169    1.53 0.011  0.160   
HLA.6DRML        2      0.18   0.088    0.80 0.012  0.611   
T1Dstatus        1      0.44   0.441    4.00 0.029  0.007 **
Residuals      119     13.12   0.110         0.867          
Total          130     15.14                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.007

Beta diversity Plot

7.1.5 Days within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.53   0.265    2.81 0.022  0.258  
seqRun      4      1.73   0.432    4.57 0.071  0.931  
Age         1      0.18   0.182    1.92 0.008  0.067 .
Parity      1      0.16   0.162    1.71 0.007  0.821  
BMI         1      0.31   0.307    3.25 0.013  0.318  
Days        1      0.13   0.131    1.39 0.005  0.030 *
Residuals 224     21.16   0.094         0.874  0.299  
Total     234     24.20                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

7.1.6 Trimester within T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.53   0.265    2.79 0.022  0.237  
seqRun      4      1.73   0.432    4.55 0.071  0.927  
Age         1      0.18   0.182    1.91 0.008  0.066 .
Parity      1      0.16   0.162    1.70 0.007  0.799  
BMI         1      0.31   0.307    3.23 0.013  0.326  
Tri         2      0.12   0.062    0.65 0.005  0.268  
Residuals 223     21.17   0.095         0.875  0.418  
Total     234     24.20                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

7.1.7 Days within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.52   0.258    1.99 0.032  0.528  
seqRun      5      0.65   0.131    1.01 0.041  0.831  
Age         1      0.50   0.499    3.85 0.031  0.396  
Parity      1      0.25   0.253    1.95 0.016  0.049 *
BMI         1      0.09   0.092    0.71 0.006  0.543  
Days        1      0.09   0.094    0.72 0.006  0.340  
Residuals 107     13.87   0.130         0.868  0.732  
Total     118     15.97                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

7.1.8 Trimester within non-T1D


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.52   0.258    1.97 0.032  0.501  
seqRun      5      0.65   0.131    1.00 0.041  0.827  
Age         1      0.50   0.499    3.81 0.031  0.383  
Parity      1      0.25   0.253    1.94 0.016  0.035 *
BMI         1      0.09   0.092    0.70 0.006  0.560  
Tri         2      0.10   0.048    0.37 0.006  0.894  
Residuals 106     13.86   0.131         0.868  0.803  
Total     118     15.97                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Beta diversity Plot

7.1.9 Other factors

7.1.9.1 Age at conception

7.1.9.1.1 Age at conception interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.732   
T1Dstatus              1       1.0   0.979    9.01 0.024  0.003 **
seqRun                 5       1.9   0.373    3.44 0.046  0.551   
Tri                    2       0.1   0.073    0.67 0.004  0.302   
Age                    1       0.3   0.322    2.96 0.008  0.828   
Parity                 1       0.2   0.159    1.46 0.004  0.986   
BMI                    1       0.2   0.211    1.95 0.005  0.913   
Age_Time_Interaction   1       0.2   0.153    1.40 0.004  0.344   
Residuals            339      36.8   0.109         0.898  0.179   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.1.2 Age at conception interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.720   
T1Dstatus              1       1.0   0.979    8.99 0.024  0.006 **
seqRun                 5       1.9   0.373    3.43 0.046  0.543   
Tri                    2       0.1   0.073    0.67 0.004  0.309   
Age                    1       0.3   0.322    2.96 0.008  0.823   
Parity                 1       0.2   0.159    1.46 0.004  0.976   
BMI                    1       0.2   0.211    1.94 0.005  0.906   
Age_Time_Interaction   1       0.1   0.069    0.63 0.002  0.500   
Residuals            339      36.9   0.109         0.900  0.193   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.1.3 Age at conception interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.737   
T1Dstatus              1       1.0   0.979    8.98 0.024  0.003 **
seqRun                 5       1.9   0.373    3.43 0.046  0.533   
Tri                    2       0.1   0.073    0.67 0.004  0.289   
Age                    1       0.3   0.322    2.95 0.008  0.836   
Parity                 1       0.2   0.159    1.46 0.004  0.984   
BMI                    1       0.2   0.211    1.94 0.005  0.922   
Age_Time_Interaction   1       0.0   0.031    0.28 0.001  0.784   
Residuals            339      36.9   0.109         0.901  0.225   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.1.4 Age at conception (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
HLA         2       0.3   0.172    1.58 0.008  0.700    
T1Dstatus   1       1.0   0.979    9.00 0.024  0.001 ***
seqRun      5       1.9   0.373    3.43 0.046  0.526    
Tri         2       0.1   0.073    0.67 0.004  0.316    
Parity      1       0.2   0.155    1.43 0.004  0.996    
BMI         1       0.2   0.210    1.93 0.005  0.920    
Age         1       0.3   0.327    3.01 0.008  0.672    
Residuals 340      37.0   0.109         0.902  0.181    
Total     353      41.0                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.2 Body max index (BMI)

7.1.9.2.1 BMI interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.730   
T1Dstatus              1       1.0   0.979    8.99 0.024  0.006 **
seqRun                 5       1.9   0.373    3.43 0.046  0.566   
Tri                    2       0.1   0.073    0.67 0.004  0.302   
Age                    1       0.3   0.322    2.95 0.008  0.826   
Parity                 1       0.2   0.159    1.46 0.004  0.984   
BMI                    1       0.2   0.211    1.94 0.005  0.907   
BMI_Time_Interaction   1       0.0   0.045    0.42 0.001  0.757   
Residuals            339      36.9   0.109         0.901  0.228   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.2.2 BMI interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.740   
T1Dstatus              1       1.0   0.979    9.00 0.024  0.003 **
seqRun                 5       1.9   0.373    3.43 0.046  0.556   
Tri                    2       0.1   0.073    0.67 0.004  0.313   
Age                    1       0.3   0.322    2.96 0.008  0.843   
Parity                 1       0.2   0.159    1.46 0.004  0.974   
BMI                    1       0.2   0.211    1.94 0.005  0.918   
BMI_Time_Interaction   1       0.1   0.078    0.72 0.002  0.409   
Residuals            339      36.9   0.109         0.900  0.193   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.2.3 BMI (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.731   
T1Dstatus              1       1.0   0.979    8.99 0.024  0.003 **
seqRun                 5       1.9   0.373    3.43 0.046  0.531   
Tri                    2       0.1   0.073    0.67 0.004  0.285   
Age                    1       0.3   0.322    2.96 0.008  0.840   
Parity                 1       0.2   0.159    1.46 0.004  0.982   
BMI                    1       0.2   0.211    1.94 0.005  0.908   
BMI_Time_Interaction   1       0.1   0.054    0.49 0.001  0.547   
Residuals            339      36.9   0.109         0.900  0.190   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.2.4 BMI (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.3   0.172    1.58 0.008  0.757   
T1Dstatus   1       1.0   0.979    9.00 0.024  0.002 **
seqRun      5       1.9   0.373    3.43 0.046  0.529   
Tri         2       0.1   0.073    0.67 0.004  0.316   
Age         1       0.3   0.322    2.96 0.008  0.822   
Parity      1       0.2   0.159    1.46 0.004  0.974   
BMI         1       0.2   0.211    1.94 0.005  0.910   
Residuals 340      37.0   0.109         0.902  0.193   
Total     353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.3 HLA type

7.1.9.3.1 HLA type interaction with time (reference: DR34 )

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.59 0.008  0.722   
T1Dstatus              1       1.0   0.979    9.04 0.024  0.004 **
Days                   1       0.2   0.227    2.10 0.006  0.086 . 
seqRun                 5       1.9   0.372    3.43 0.045  0.531   
Age                    1       0.3   0.309    2.86 0.008  0.818   
Parity                 1       0.2   0.153    1.41 0.004  0.994   
BMI                    1       0.2   0.205    1.89 0.005  0.936   
HLA_Time_Interaction   1       0.1   0.099    0.91 0.002  0.972   
Residuals            340      36.8   0.108         0.898  0.154   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.3.2 HLA type interaction with time (reference: DRXX)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.58 0.008  0.709   
T1Dstatus              1       1.0   0.979    9.02 0.024  0.006 **
Days                   1       0.2   0.227    2.09 0.006  0.091 . 
seqRun                 5       1.9   0.372    3.42 0.045  0.577   
Age                    1       0.3   0.309    2.85 0.008  0.811   
Parity                 1       0.2   0.153    1.41 0.004  0.989   
BMI                    1       0.2   0.205    1.89 0.005  0.936   
HLA_Time_Interaction   1       0.0   0.008    0.07 0.000  1.000   
Residuals            340      36.9   0.109         0.900  0.195   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.3.3 HLA type interaction with time (reference: Group3o4)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.59 0.008  0.735   
T1Dstatus              1       1.0   0.979    9.03 0.024  0.006 **
Days                   1       0.2   0.227    2.10 0.006  0.098 . 
seqRun                 5       1.9   0.372    3.43 0.045  0.565   
Age                    1       0.3   0.309    2.85 0.008  0.791   
Parity                 1       0.2   0.153    1.41 0.004  0.991   
BMI                    1       0.2   0.205    1.89 0.005  0.934   
HLA_Time_Interaction   1       0.1   0.056    0.52 0.001  1.000   
Residuals            340      36.9   0.108         0.899  0.218   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.3.4 HLA type (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
Days        1       0.2   0.246    2.27 0.006  0.068 . 
seqRun      5       1.8   0.356    3.29 0.043  0.623   
Age         1       0.3   0.345    3.19 0.008  0.565   
Parity      1       0.2   0.189    1.75 0.005  0.990   
BMI         1       0.3   0.260    2.40 0.006  0.152   
T1Dstatus   1       0.8   0.850    7.85 0.021  0.006 **
HLA         2       0.4   0.203    1.87 0.010  0.577   
Residuals 341      36.9   0.108         0.901  0.129   
Total     353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.4 Parity

7.1.9.4.1 Parity interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                         Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                       2       0.3   0.172    1.59 0.008  0.724   
T1Dstatus                 1       1.0   0.979    9.04 0.024  0.002 **
Days                      1       0.2   0.227    2.10 0.006  0.105   
seqRun                    5       1.9   0.372    3.43 0.045  0.537   
Age                       1       0.3   0.309    2.86 0.008  0.809   
Parity                    1       0.2   0.153    1.41 0.004  0.990   
BMI                       1       0.2   0.205    1.89 0.005  0.939   
Parity_Time_Interaction   1       0.1   0.113    1.05 0.003  0.068 . 
Residuals               340      36.8   0.108         0.898  0.107   
Total                   353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.4.2 Parity (no interaction but within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA        2      0.24  0.1222   1.150 0.041  0.329  
T1Dstatus  1      0.11  0.1066   1.003 0.018  0.407  
seqRun     1      0.23  0.2273   2.139 0.038  0.012 *
Age        1      0.19  0.1908   1.796 0.032  0.156  
BMI        1      0.07  0.0679   0.639 0.011  0.894  
Parity     1      0.09  0.0949   0.894 0.016  0.147  
Residuals 48      5.10  0.1063         0.846  0.133  
Total     55      6.03                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.4.3 Parity (no interaction but within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.21   0.107    0.94 0.011  0.735  
T1Dstatus   1      0.52   0.516    4.56 0.028  0.018 *
seqRun      1      0.59   0.595    5.25 0.032  0.110  
Age         1      0.15   0.154    1.36 0.008  0.968  
BMI         1      0.13   0.132    1.17 0.007  0.328  
Parity      1      0.07   0.073    0.65 0.004  0.989  
Residuals 150     16.99   0.113         0.910  0.106  
Total     157     18.68                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.4.4 Parity (no interaction but within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.21   0.107    0.97 0.013  0.618  
T1Dstatus   1      0.45   0.449    4.09 0.028  0.012 *
seqRun      1      0.57   0.572    5.22 0.035  0.232  
Age         1      0.12   0.120    1.10 0.007  0.795  
BMI         1      0.09   0.094    0.86 0.006  0.873  
Parity      1      0.22   0.224    2.04 0.014  0.818  
Residuals 132     14.48   0.110         0.896  0.059 .
Total     139     16.16                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.5 Mode of delivery

7.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.61 0.008  0.726   
T1Dstatus              1       1.0   0.979    9.17 0.024  0.003 **
MOD                    2       0.6   0.309    2.90 0.015  0.245   
Days                   1       0.2   0.228    2.14 0.006  0.115   
seqRun                 5       1.9   0.384    3.60 0.047  0.522   
Age                    1       0.4   0.438    4.10 0.011  0.050 * 
Parity                 1       0.1   0.147    1.38 0.004  0.979   
BMI                    1       0.2   0.153    1.44 0.004  0.989   
MOD_Time_Interaction   1       0.1   0.094    0.88 0.002  0.947   
Residuals            338      36.1   0.107         0.880  0.074 . 
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.3   0.172    1.62 0.008  0.726   
T1Dstatus              1       1.0   0.979    9.20 0.024  0.002 **
MOD                    2       0.6   0.309    2.90 0.015  0.234   
Days                   1       0.2   0.228    2.14 0.006  0.096 . 
seqRun                 5       1.9   0.384    3.61 0.047  0.528   
Age                    1       0.4   0.438    4.11 0.011  0.055 . 
Parity                 1       0.1   0.147    1.38 0.004  0.978   
BMI                    1       0.2   0.153    1.44 0.004  0.988   
MOD_Time_Interaction   1       0.2   0.180    1.69 0.004  1.000   
Residuals            338      36.0   0.106         0.878  0.295   
Total                353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.5.3 Mode of delivery interaction with time (reference: Labour)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
HLA                    2       0.3   0.172    1.61 0.008  0.717    
T1Dstatus              1       1.0   0.979    9.17 0.024  0.001 ***
MOD                    2       0.6   0.309    2.90 0.015  0.241    
Days                   1       0.2   0.228    2.14 0.006  0.109    
seqRun                 5       1.9   0.384    3.60 0.047  0.513    
Age                    1       0.4   0.438    4.10 0.011  0.061 .  
Parity                 1       0.1   0.147    1.38 0.004  0.987    
BMI                    1       0.2   0.153    1.44 0.004  0.991    
MOD_Time_Interaction   1       0.1   0.073    0.69 0.002  1.000    
Residuals            338      36.1   0.107         0.880  0.416    
Total                353      41.0                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.5.4 Mode of delivery (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
Days        1       0.2   0.246    2.30 0.006  0.066 . 
seqRun      5       1.8   0.356    3.34 0.043  0.595   
Age         1       0.3   0.345    3.23 0.008  0.586   
Parity      1       0.2   0.189    1.77 0.005  0.994   
BMI         1       0.3   0.260    2.43 0.006  0.162   
HLA         2       0.3   0.153    1.43 0.007  0.777   
T1Dstatus   1       0.9   0.950    8.90 0.023  0.005 **
MOD         2       0.8   0.377    3.53 0.018  0.102   
Residuals 339      36.2   0.107         0.882  0.054 . 
Total     353      41.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.6 Carbohydrate intake

7.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2       0.3   0.172    1.63 0.009  0.711   
T1Dstatus               1       0.6   0.650    6.16 0.018  0.025 * 
Carbs                   1       0.3   0.305    2.89 0.008  0.270   
seqRun                  5       2.0   0.400    3.79 0.054  0.689   
Tri                     2       0.1   0.051    0.48 0.003  0.443   
Age                     1       0.3   0.320    3.04 0.009  0.771   
Parity                  1       0.2   0.183    1.73 0.005  0.953   
BMI                     1       0.2   0.236    2.24 0.006  0.668   
Carb_Time_Interaction   1       0.2   0.179    1.69 0.005  0.010 **
Residuals             310      32.7   0.106         0.883  0.403   
Total                 325      37.0                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       0.3   0.172    1.63 0.009  0.722  
T1Dstatus               1       0.6   0.650    6.16 0.018  0.033 *
Carbs                   1       0.3   0.305    2.89 0.008  0.266  
seqRun                  5       2.0   0.400    3.79 0.054  0.717  
Tri                     2       0.1   0.051    0.48 0.003  0.485  
Age                     1       0.3   0.320    3.04 0.009  0.766  
Parity                  1       0.2   0.183    1.73 0.005  0.947  
BMI                     1       0.2   0.236    2.24 0.006  0.653  
Carb_Time_Interaction   1       0.2   0.182    1.73 0.005  0.097 .
Residuals             310      32.7   0.106         0.883  0.473  
Total                 325      37.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                     2       0.3   0.172    1.63 0.009  0.715  
T1Dstatus               1       0.6   0.650    6.15 0.018  0.027 *
Carbs                   1       0.3   0.305    2.88 0.008  0.247  
seqRun                  5       2.0   0.400    3.79 0.054  0.700  
Tri                     2       0.1   0.051    0.48 0.003  0.463  
Age                     1       0.3   0.320    3.03 0.009  0.770  
Parity                  1       0.2   0.183    1.73 0.005  0.946  
BMI                     1       0.2   0.236    2.24 0.006  0.677  
Carb_Time_Interaction   1       0.1   0.138    1.30 0.004  0.055 .
Residuals             310      32.8   0.106         0.884  0.440  
Total                 325      37.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.6.4 Carbohydrate (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3      0.37   0.125   1.172 0.070  0.003 ** 
Age        1      0.14   0.143   1.341 0.027  0.003 ** 
Parity     1      0.11   0.106   0.997 0.020  0.003 ** 
BMI        1      0.10   0.101   0.942 0.019  0.001 ***
HLA        2      0.25   0.127   1.188 0.047  0.294    
T1Dstatus  1      0.14   0.142   1.335 0.026  0.243    
Carbs      1      0.11   0.105   0.985 0.020  0.422    
Residuals 39      4.16   0.107         0.772  0.273    
Total     49      5.38                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.6.5 Carbohydrate (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun      4      1.04   0.260   2.411 0.063  0.001 ***
Age         1      0.19   0.195   1.809 0.012  0.847    
Parity      1      0.12   0.121   1.127 0.007  0.846    
BMI         1      0.14   0.136   1.263 0.008  0.925    
HLA         2      0.15   0.077   0.719 0.009  0.911    
T1Dstatus   1      0.33   0.331   3.069 0.020  0.045 *  
Carbs       1      0.28   0.276   2.563 0.017  0.074 .  
Residuals 132     14.22   0.108         0.863  0.154    
Total     143     16.47                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.6.6 Carbohydrate (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      4      0.88  0.2211   2.021 0.059   0.58  
Age         1      0.14  0.1405   1.284 0.009   0.35  
Parity      1      0.19  0.1883   1.721 0.012   0.92  
BMI         1      0.15  0.1536   1.404 0.010   0.31  
HLA         2      0.16  0.0778   0.711 0.010   0.81  
T1Dstatus   1      0.31  0.3148   2.877 0.021   0.04 *
Carbs       1      0.11  0.1080   0.987 0.007   0.48  
Residuals 120     13.13  0.1094         0.871   0.67  
Total     131     15.08                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.7 Fibre intake

7.1.9.7.1 Fibre interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
HLA                      2       0.3   0.172    1.64 0.009  0.709    
T1Dstatus                1       0.6   0.650    6.19 0.018  0.024 *  
Fiber                    1       0.3   0.253    2.41 0.007  0.363    
seqRun                   5       2.2   0.447    4.26 0.060  0.520    
Tri                      2       0.1   0.049    0.47 0.003  0.506    
Age                      1       0.3   0.320    3.05 0.009  0.770    
Parity                   1       0.2   0.174    1.66 0.005  0.981    
BMI                      1       0.2   0.215    2.05 0.006  0.833    
Fiber_Time_Interaction   1       0.2   0.202    1.93 0.005  0.001 ***
Residuals              310      32.5   0.105         0.879  0.228    
Total                  325      37.0                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.7.2 Fibre interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       0.3   0.172    1.64 0.009  0.725  
T1Dstatus                1       0.6   0.650    6.18 0.018  0.027 *
Fiber                    1       0.3   0.253    2.41 0.007  0.360  
seqRun                   5       2.2   0.447    4.25 0.060  0.500  
Tri                      2       0.1   0.049    0.47 0.003  0.467  
Age                      1       0.3   0.320    3.05 0.009  0.787  
Parity                   1       0.2   0.174    1.66 0.005  0.975  
BMI                      1       0.2   0.215    2.04 0.006  0.826  
Fiber_Time_Interaction   1       0.1   0.138    1.31 0.004  0.842  
Residuals              310      32.6   0.105         0.880  0.438  
Total                  325      37.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.7.3 Fibre interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2       0.3   0.172    1.64 0.009  0.727  
T1Dstatus                1       0.6   0.650    6.18 0.018  0.026 *
Fiber                    1       0.3   0.253    2.41 0.007  0.356  
seqRun                   5       2.2   0.447    4.25 0.060  0.490  
Tri                      2       0.1   0.049    0.47 0.003  0.506  
Age                      1       0.3   0.320    3.05 0.009  0.750  
Parity                   1       0.2   0.174    1.66 0.005  0.972  
BMI                      1       0.2   0.215    2.05 0.006  0.841  
Fiber_Time_Interaction   1       0.2   0.187    1.78 0.005  0.531  
Residuals              310      32.6   0.105         0.879  0.362  
Total                  325      37.0                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.7.4 Fibre (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3      0.37   0.125   1.154 0.070  0.005 ** 
Age        1      0.14   0.143   1.321 0.027  0.005 ** 
Parity     1      0.11   0.106   0.982 0.020  0.005 ** 
BMI        1      0.10   0.101   0.928 0.019  0.001 ***
HLA        2      0.25   0.127   1.170 0.047  0.296    
T1Dstatus  1      0.14   0.142   1.315 0.026  0.231    
Fiber      1      0.04   0.043   0.397 0.008  0.864    
Residuals 39      4.22   0.108         0.784  0.412    
Total     49      5.38                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.7.5 Fibre (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun      4      1.04   0.260   2.393 0.063  0.001 ***
Age         1      0.19   0.195   1.796 0.012  0.847    
Parity      1      0.12   0.121   1.119 0.007  0.854    
BMI         1      0.14   0.136   1.253 0.008  0.929    
HLA         2      0.15   0.077   0.714 0.009  0.911    
T1Dstatus   1      0.33   0.331   3.046 0.020  0.054 .  
Fiber       1      0.17   0.168   1.550 0.010  0.303    
Residuals 132     14.33   0.109         0.870  0.314    
Total     143     16.47                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.7.6 Fibre (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
seqRun      4      0.88   0.221    2.07 0.059  0.514   
Age         1      0.14   0.140    1.32 0.009  0.389   
Parity      1      0.19   0.188    1.76 0.012  0.916   
BMI         1      0.15   0.154    1.44 0.010  0.333   
HLA         2      0.16   0.078    0.73 0.010  0.792   
T1Dstatus   1      0.31   0.315    2.95 0.021  0.040 * 
Fiber       1      0.42   0.423    3.96 0.028  0.006 **
Residuals 120     12.82   0.107         0.850  0.413   
Total     131     15.08                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.8 1,5-AG (glucose control measurement)

7.1.9.8.1 1,5-AG interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                    2       0.4   0.178    1.66 0.009  0.705   
T1Dstatus              1       1.0   1.050    9.78 0.028  0.002 **
Days                   1       0.2   0.229    2.14 0.006  0.018 * 
seqRun                 4       1.6   0.402    3.74 0.043  0.090 . 
Age                    1       0.4   0.365    3.40 0.010  0.733   
Parity                 1       0.1   0.148    1.38 0.004  0.992   
BMI                    1       0.2   0.165    1.54 0.004  0.929   
AG15                   1       0.3   0.331    3.08 0.009  0.340   
AG15_T1D_Interaction   1       0.2   0.152    1.42 0.004  1.000   
Residuals            311      33.4   0.107         0.883  0.088 . 
Total                324      37.8                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.8.2 1,5-AG within T1D women

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.56   0.281    3.00 0.026  0.181  
Days        1      0.17   0.168    1.80 0.008  0.011 *
seqRun      4      1.42   0.355    3.79 0.065  0.984  
Age         1      0.18   0.183    1.96 0.008  0.035 *
Parity      1      0.14   0.137    1.47 0.006  0.730  
BMI         1      0.26   0.256    2.74 0.012  0.255  
AG15        1      0.21   0.209    2.23 0.010  0.686  
Residuals 202     18.89   0.094         0.866  0.288  
Total     213     21.83                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.8.3 1,5-AG interaction with time (within non-T1D women)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.58   0.290    2.28 0.038  0.447  
Days        1      0.18   0.181    1.42 0.012  0.128  
seqRun      3      0.45   0.152    1.19 0.030  0.936  
Age         1      0.51   0.508    3.99 0.034  0.558  
Parity      1      0.26   0.256    2.01 0.017  0.069 .
BMI         1      0.07   0.070    0.55 0.005  0.870  
AG15        1      0.29   0.293    2.30 0.019  0.234  
Residuals 100     12.73   0.127         0.845  0.413  
Total     110     15.08                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
7.1.9.8.4 1,5-AG (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA         2       0.4   0.178    1.66 0.009  0.696   
T1Dstatus   1       1.0   1.050    9.77 0.028  0.003 **
Days        1       0.2   0.229    2.13 0.006  0.024 * 
seqRun      4       1.6   0.402    3.74 0.043  0.091 . 
Age         1       0.4   0.365    3.40 0.010  0.721   
Parity      1       0.1   0.148    1.38 0.004  0.992   
BMI         1       0.2   0.165    1.54 0.004  0.926   
AG15        1       0.3   0.331    3.08 0.009  0.372   
Residuals 312      33.5   0.107         0.887  0.015 * 
Total     324      37.8                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.1.9.9 Pre-eclampsia (within T1D women)


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

              Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA            2      0.53   0.265    2.81 0.022  0.256  
Days           1      0.14   0.138    1.46 0.006  0.036 *
seqRun         4      1.71   0.429    4.54 0.071  0.943  
Age            1      0.17   0.171    1.81 0.007  0.127  
Parity         1      0.16   0.161    1.71 0.007  0.821  
BMI            1      0.32   0.324    3.44 0.013  0.160  
Preeclampsia   1      0.11   0.108    1.14 0.004  0.365  
Residuals    223     21.05   0.094         0.870  0.295  
Total        234     24.20                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

7.2 Differential abundance analysis Family taxonomic level

Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type

       nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down               0  0  0  0        0        0        0         1         1         2
NotSig            33 33 25 33       33       33       32        32        32        31
Up                 0  0  8  0        0        0        1         0         0         0
       noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down             0           0           0
NotSig          33          31          33
Up               0           2           0

Results for contrasts with significant (or borderline significant) differences shown below

7.2.1 Across all trimesters (T1D vs non-T1D)

[1] Classification LogFC          P.Val          adj.P.Val      nonT1D:mean%  
[6] Prev%          T1D:mean%      T1D:Prev%      Feature       
<0 rows> (or 0-length row.names)

7.2.2 Only Trimester 1 (nonT1D vs T1D)

       Classification LogFC   P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Desulfovibrionaceae  1.63 0.00364    0.0601        0.353  83.3     0.154      65.8

7.2.3 Only Trimester 2 (nonT1D vs T1D)

   Classification LogFC   P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Lachnospiraceae  0.53 0.00878    0.0483         17.3   100      15.3       100

7.2.4 Only Trimester 3 (nonT1D vs T1D)

[1] "No DA taxa"

7.2.5 T1 vs T2 (T1D and non-T1D data)

[1] "No DA taxa"

7.2.6 T2 vs T3 (T1D and non-T1D data)

[1] "No DA taxa"

Nothing left after filtering by prevalence and LogFC

7.2.7 T1 vs T3 (T1D and non-T1D data)

   Classification LogFC   P.Val adj.P.Val mean% Prev%
1 Pasteurellaceae 0.835 0.00095    0.0313 0.095  33.9
2 Pasteurellaceae 0.835 0.00095    0.0313 0.081  32.3
3 Pasteurellaceae 0.835 0.00095    0.0313 0.061  27.1

7.2.8 T1 vs T2 (in women with T1D)

    Classification LogFC   P.Val adj.P.Val mean% Prev%
1 Clostridiaceae 1 -1.01 0.00143    0.0473 0.187  44.7
2 Clostridiaceae 1 -1.01 0.00143    0.0473 0.458  59.8

7.2.9 T2 vs T3 (in women with T1D)

  Classification  LogFC    P.Val adj.P.Val mean% Prev%
1 Peptococcaceae -0.543 0.000111   0.00366 0.007  10.3
2 Peptococcaceae -0.543 0.000111   0.00366 0.025  23.3

7.2.10 T1 vs T3 (in women with T1D)

  Classification  LogFC   P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
1 Bacteroidaceae -0.533 0.00216    0.0357     32.5    97.4     35.4     100

7.2.11 T1 vs T2 (in women without T1D)

[1] "No DA taxa"

7.2.12 T2 vs T3 (in women without T1D)

[1] Classification LogFC          P.Val          adj.P.Val      T2:mean%      
[6] T2Prev%        T3:mean%       T3Prev%       
<0 rows> (or 0-length row.names)

7.2.13 T1 vs T3 (in women without T1D)

[1] "No DA taxa"

8 Order taxonomic level

8.1 Microbial community composition analysis at Order level (Beta diversity analysis)

8.1.1 Interaction between T1D status and Time


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun                 5      0.90  0.1798    4.54 0.060   0.83
Days                   1      0.10  0.0966    2.44 0.006   0.10
T1D_Time_Interaction   1      0.07  0.0661    1.67 0.004   0.16
Age                    1      0.03  0.0257    0.65 0.002   0.65
Parity                 1      0.13  0.1336    3.37 0.009   0.98
BMI                    1      0.11  0.1094    2.76 0.007   0.58
HLA                    2      0.11  0.0568    1.43 0.008   0.51
T1Dstatus              1      0.02  0.0160    0.40 0.001   0.86
Residuals            340     13.47  0.0396         0.902   0.77
Total                353     14.93                 1.000       
[1] 0.156

8.1.2 Other factors

8.1.2.1 Age at conception

8.1.2.1.1 Age at conception interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.86 0.010   0.43
T1Dstatus              1      0.06  0.0608    1.54 0.004   0.42
seqRun                 5      0.91  0.1826    4.62 0.061   0.67
Tri                    2      0.07  0.0333    0.84 0.004   0.22
Age                    1      0.03  0.0288    0.73 0.002   0.41
Parity                 1      0.12  0.1174    2.97 0.008   0.97
BMI                    1      0.10  0.0969    2.45 0.006   0.83
Age_Time_Interaction   1      0.10  0.0998    2.53 0.007   0.17
Residuals            339     13.40  0.0395         0.898   0.67
Total                353     14.93                 1.000       
8.1.2.1.2 Age at conception interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.86 0.010   0.47
T1Dstatus              1      0.06  0.0608    1.54 0.004   0.44
seqRun                 5      0.91  0.1826    4.62 0.061   0.64
Tri                    2      0.07  0.0333    0.84 0.004   0.23
Age                    1      0.03  0.0288    0.73 0.002   0.38
Parity                 1      0.12  0.1174    2.97 0.008   0.97
BMI                    1      0.10  0.0969    2.45 0.006   0.82
Age_Time_Interaction   1      0.10  0.0954    2.41 0.006   0.17
Residuals            339     13.40  0.0395         0.898   0.66
Total                353     14.93                 1.000       
8.1.2.1.3 Age at conception interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.84 0.010   0.42
T1Dstatus              1      0.06  0.0608    1.53 0.004   0.43
seqRun                 5      0.91  0.1826    4.59 0.061   0.65
Tri                    2      0.07  0.0333    0.84 0.004   0.22
Age                    1      0.03  0.0288    0.72 0.002   0.34
Parity                 1      0.12  0.1174    2.95 0.008   0.97
BMI                    1      0.10  0.0969    2.43 0.006   0.83
Age_Time_Interaction   1      0.01  0.0092    0.23 0.001   0.66
Residuals            339     13.49  0.0398         0.904   0.80
Total                353     14.93                 1.000       
8.1.2.1.4 Age at conception (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.15  0.0734    1.85 0.010   0.44
T1Dstatus   1      0.06  0.0608    1.53 0.004   0.45
seqRun      5      0.91  0.1826    4.60 0.061   0.68
Tri         2      0.07  0.0333    0.84 0.004   0.23
Parity      1      0.12  0.1155    2.91 0.008   0.98
BMI         1      0.10  0.0960    2.42 0.006   0.84
Age         1      0.03  0.0315    0.79 0.002   0.24
Residuals 340     13.50  0.0397         0.904   0.79
Total     353     14.93                 1.000       

8.1.2.2 Body max index (BMI)

8.1.2.2.1 BMI interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.84 0.010   0.44
T1Dstatus              1      0.06  0.0608    1.53 0.004   0.42
seqRun                 5      0.91  0.1826    4.59 0.061   0.69
Tri                    2      0.07  0.0333    0.84 0.004   0.22
Age                    1      0.03  0.0288    0.72 0.002   0.39
Parity                 1      0.12  0.1174    2.95 0.008   0.97
BMI                    1      0.10  0.0969    2.43 0.006   0.80
BMI_Time_Interaction   1      0.00  0.0037    0.09 0.000   0.96
Residuals            339     13.49  0.0398         0.904   0.88
Total                353     14.93                 1.000       
8.1.2.2.2 BMI interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.85 0.010   0.41
T1Dstatus              1      0.06  0.0608    1.53 0.004   0.46
seqRun                 5      0.91  0.1826    4.60 0.061   0.66
Tri                    2      0.07  0.0333    0.84 0.004   0.22
Age                    1      0.03  0.0288    0.72 0.002   0.35
Parity                 1      0.12  0.1174    2.96 0.008   0.98
BMI                    1      0.10  0.0969    2.44 0.006   0.82
BMI_Time_Interaction   1      0.04  0.0416    1.05 0.003   0.55
Residuals            339     13.46  0.0397         0.901   0.81
Total                353     14.93                 1.000       
8.1.2.2.3 BMI (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.85 0.010   0.47
T1Dstatus              1      0.06  0.0608    1.53 0.004   0.40
seqRun                 5      0.91  0.1826    4.60 0.061   0.64
Tri                    2      0.07  0.0333    0.84 0.004   0.22
Age                    1      0.03  0.0288    0.72 0.002   0.36
Parity                 1      0.12  0.1174    2.96 0.008   0.97
BMI                    1      0.10  0.0969    2.44 0.006   0.83
BMI_Time_Interaction   1      0.04  0.0436    1.10 0.003   0.12
Residuals            339     13.45  0.0397         0.901   0.72
Total                353     14.93                 1.000       
8.1.2.2.4 BMI (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.15  0.0734    1.85 0.010   0.46
T1Dstatus   1      0.06  0.0608    1.53 0.004   0.44
seqRun      5      0.91  0.1826    4.60 0.061   0.65
Tri         2      0.07  0.0333    0.84 0.004   0.23
Age         1      0.03  0.0288    0.72 0.002   0.37
Parity      1      0.12  0.1174    2.96 0.008   0.96
BMI         1      0.10  0.0969    2.44 0.006   0.81
Residuals 340     13.50  0.0397         0.904   0.78
Total     353     14.93                 1.000       

8.1.2.3 HLA type

8.1.2.3.1 HLA type interaction with time (reference: DR34 )

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.85 0.010   0.43
T1Dstatus              1      0.06  0.0608    1.54 0.004   0.43
Days                   1      0.07  0.0695    1.76 0.005   0.12
seqRun                 5      0.95  0.1892    4.78 0.063   0.55
Age                    1      0.03  0.0273    0.69 0.002   0.50
Parity                 1      0.11  0.1130    2.85 0.008   0.96
BMI                    1      0.09  0.0929    2.35 0.006   0.89
HLA_Time_Interaction   1      0.02  0.0184    0.47 0.001   0.97
Residuals            340     13.45  0.0396         0.901   0.80
Total                353     14.93                 1.000       
8.1.2.3.2 HLA type interaction with time (reference: DRXX)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.85 0.010   0.44
T1Dstatus              1      0.06  0.0608    1.53 0.004   0.45
Days                   1      0.07  0.0695    1.76 0.005   0.14
seqRun                 5      0.95  0.1892    4.78 0.063   0.57
Age                    1      0.03  0.0273    0.69 0.002   0.50
Parity                 1      0.11  0.1130    2.85 0.008   0.96
BMI                    1      0.09  0.0929    2.35 0.006   0.87
HLA_Time_Interaction   1      0.00  0.0027    0.07 0.000   1.00
Residuals            340     13.47  0.0396         0.902   0.76
Total                353     14.93                 1.000       
8.1.2.3.3 HLA type interaction with time (reference: Group3o4)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.15  0.0734    1.85 0.010   0.45
T1Dstatus              1      0.06  0.0608    1.54 0.004   0.44
Days                   1      0.07  0.0695    1.76 0.005   0.15
seqRun                 5      0.95  0.1892    4.78 0.063   0.55
Age                    1      0.03  0.0273    0.69 0.002   0.52
Parity                 1      0.11  0.1130    2.85 0.008   0.96
BMI                    1      0.09  0.0929    2.35 0.006   0.87
HLA_Time_Interaction   1      0.02  0.0161    0.41 0.001   0.99
Residuals            340     13.46  0.0396         0.901   0.80
Total                353     14.93                 1.000       
8.1.2.3.4 HLA type (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
Days        1      0.07  0.0730    1.85 0.005   0.14
seqRun      5      0.92  0.1845    4.67 0.062   0.76
Age         1      0.03  0.0266    0.67 0.002   0.58
Parity      1      0.15  0.1451    3.67 0.010   0.95
BMI         1      0.12  0.1196    3.03 0.008   0.38
T1Dstatus   1      0.05  0.0528    1.34 0.004   0.47
HLA         2      0.12  0.0583    1.48 0.008   0.55
Residuals 341     13.47  0.0395         0.902   0.73
Total     353     14.93                 1.000       

8.1.2.4 Parity

8.1.2.4.1 Parity interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                         Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                       2      0.15  0.0734    1.86 0.010  0.429  
T1Dstatus                 1      0.06  0.0608    1.54 0.004  0.408  
Days                      1      0.07  0.0695    1.76 0.005  0.143  
seqRun                    5      0.95  0.1892    4.79 0.063  0.569  
Age                       1      0.03  0.0273    0.69 0.002  0.506  
Parity                    1      0.11  0.1130    2.86 0.008  0.961  
BMI                       1      0.09  0.0929    2.36 0.006  0.874  
Parity_Time_Interaction   1      0.06  0.0564    1.43 0.004  0.051 .
Residuals               340     13.41  0.0395         0.899  0.568  
Total                   353     14.93                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.4.2 Parity (no interaction but within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA        2     0.039  0.0194   0.526 0.019  0.716  
T1Dstatus  1     0.015  0.0146   0.397 0.007  0.730  
seqRun     1     0.038  0.0383   1.042 0.019  0.247  
Age        1     0.102  0.1024   2.782 0.050  0.232  
BMI        1     0.014  0.0143   0.388 0.007  0.797  
Parity     1     0.053  0.0529   1.439 0.026  0.026 *
Residuals 48     1.766  0.0368         0.871  0.612  
Total     55     2.028                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.4.3 Parity (no interaction but within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.09   0.047    1.12 0.014   0.48
T1Dstatus   1      0.03   0.027    0.64 0.004   0.59
seqRun      1      0.33   0.333    7.85 0.048   0.42
Age         1      0.03   0.026    0.61 0.004   0.95
BMI         1      0.01   0.014    0.32 0.002   0.24
Parity      1      0.05   0.050    1.18 0.007   0.93
Residuals 150      6.35   0.042         0.921   0.86
Total     157      6.89                 1.000       
8.1.2.4.4 Parity (no interaction but within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.10   0.049    1.24 0.016  0.329  
T1Dstatus   1      0.04   0.039    1.00 0.007  0.344  
seqRun      1      0.38   0.382    9.75 0.064  0.642  
Age         1      0.02   0.019    0.48 0.003  0.013 *
BMI         1      0.08   0.075    1.93 0.013  0.808  
Parity      1      0.19   0.193    4.94 0.032  0.885  
Residuals 132      5.17   0.039         0.865  0.641  
Total     139      5.97                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

8.1.2.5 Mode of delivery

8.1.2.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2      0.15  0.0734    1.86 0.010  0.450  
T1Dstatus              1      0.06  0.0608    1.54 0.004  0.409  
MOD                    2      0.12  0.0595    1.50 0.008  0.526  
Days                   1      0.07  0.0728    1.84 0.005  0.117  
seqRun                 5      0.92  0.1830    4.63 0.061  0.663  
Age                    1      0.05  0.0454    1.15 0.003  0.026 *
Parity                 1      0.11  0.1141    2.89 0.008  0.908  
BMI                    1      0.07  0.0660    1.67 0.004  0.949  
MOD_Time_Interaction   1      0.02  0.0238    0.60 0.002  0.866  
Residuals            338     13.36  0.0395         0.895  0.819  
Total                353     14.93                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.5.2 Mode of delivery interaction with time (reference: Elective caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2      0.15  0.0734    1.86 0.010  0.448  
T1Dstatus              1      0.06  0.0608    1.54 0.004  0.446  
MOD                    2      0.12  0.0595    1.50 0.008  0.551  
Days                   1      0.07  0.0728    1.84 0.005  0.135  
seqRun                 5      0.92  0.1830    4.63 0.061  0.643  
Age                    1      0.05  0.0454    1.15 0.003  0.022 *
Parity                 1      0.11  0.1141    2.88 0.008  0.921  
BMI                    1      0.07  0.0660    1.67 0.004  0.960  
MOD_Time_Interaction   1      0.02  0.0168    0.43 0.001  0.797  
Residuals            338     13.37  0.0396         0.896  0.805  
Total                353     14.93                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.5.3 Mode of delivery interaction with time (reference: Labour)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2      0.15  0.0734    1.85 0.010  0.423  
T1Dstatus              1      0.06  0.0608    1.54 0.004  0.463  
MOD                    2      0.12  0.0595    1.50 0.008  0.552  
Days                   1      0.07  0.0728    1.84 0.005  0.124  
seqRun                 5      0.92  0.1830    4.62 0.061  0.643  
Age                    1      0.05  0.0454    1.15 0.003  0.017 *
Parity                 1      0.11  0.1141    2.88 0.008  0.913  
BMI                    1      0.07  0.0660    1.67 0.004  0.964  
MOD_Time_Interaction   1      0.01  0.0059    0.15 0.000  1.000  
Residuals            338     13.38  0.0396         0.896  0.843  
Total                353     14.93                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.5.4 Mode of delivery (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
Days        1      0.07  0.0730    1.85 0.005   0.13
seqRun      5      0.92  0.1845    4.67 0.062   0.76
Age         1      0.03  0.0266    0.67 0.002   0.60
Parity      1      0.15  0.1451    3.67 0.010   0.94
BMI         1      0.12  0.1196    3.03 0.008   0.38
HLA         2      0.11  0.0533    1.35 0.007   0.57
T1Dstatus   1      0.06  0.0627    1.59 0.004   0.39
MOD         2      0.08  0.0419    1.06 0.006   0.66
Residuals 339     13.39  0.0395         0.897   0.80
Total     353     14.93                 1.000       

8.1.2.6 Carbohydrate intake

8.1.2.6.1 Carbohydrate interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                     2      0.17  0.0831    2.13 0.012   0.40
T1Dstatus               1      0.09  0.0930    2.38 0.007   0.28
Carbs                   1      0.09  0.0851    2.18 0.006   0.32
seqRun                  5      0.88  0.1755    4.49 0.065   0.78
Tri                     2      0.02  0.0091    0.23 0.001   0.82
Age                     1      0.03  0.0261    0.67 0.002   0.97
Parity                  1      0.13  0.1344    3.44 0.010   0.89
BMI                     1      0.05  0.0507    1.30 0.004   0.91
Carb_Time_Interaction   1      0.00  0.0007    0.02 0.000   1.00
Residuals             310     12.12  0.0391         0.893   0.90
Total                 325     13.58                 1.000       
8.1.2.6.2 Carbohydrate interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2      0.17  0.0831    2.16 0.012  0.393   
T1Dstatus               1      0.09  0.0930    2.41 0.007  0.295   
Carbs                   1      0.09  0.0851    2.21 0.006  0.303   
seqRun                  5      0.88  0.1755    4.55 0.065  0.818   
Tri                     2      0.02  0.0091    0.24 0.001  0.824   
Age                     1      0.03  0.0261    0.68 0.002  0.968   
Parity                  1      0.13  0.1344    3.49 0.010  0.897   
BMI                     1      0.05  0.0507    1.31 0.004  0.906   
Carb_Time_Interaction   1      0.17  0.1743    4.52 0.013  0.002 **
Residuals             310     11.95  0.0386         0.880  0.543   
Total                 325     13.58                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.6.3 Carbohydrate interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2      0.17  0.0831    2.15 0.012  0.404   
T1Dstatus               1      0.09  0.0930    2.40 0.007  0.300   
Carbs                   1      0.09  0.0851    2.20 0.006  0.342   
seqRun                  5      0.88  0.1755    4.53 0.065  0.805   
Tri                     2      0.02  0.0091    0.23 0.001  0.797   
Age                     1      0.03  0.0261    0.67 0.002  0.963   
Parity                  1      0.13  0.1344    3.47 0.010  0.903   
BMI                     1      0.05  0.0507    1.31 0.004  0.899   
Carb_Time_Interaction   1      0.12  0.1161    3.00 0.009  0.003 **
Residuals             310     12.01  0.0387         0.885  0.669   
Total                 325     13.58                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.6.4 Carbohydrate (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3     0.158  0.0527   1.710 0.099  0.001 ***
Age        1     0.017  0.0171   0.554 0.011  0.001 ***
Parity     1     0.047  0.0466   1.514 0.029  0.001 ***
BMI        1     0.062  0.0622   2.019 0.039  0.001 ***
HLA        2     0.035  0.0173   0.561 0.022  0.722    
T1Dstatus  1     0.053  0.0527   1.710 0.033  0.164    
Carbs      1     0.022  0.0225   0.730 0.014  0.479    
Residuals 39     1.201  0.0308         0.753  0.531    
Total     49     1.595                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.6.5 Carbohydrate (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun      4      0.42  0.1059    2.55 0.067  0.001 ***
Age         1      0.06  0.0632    1.52 0.010  0.633    
Parity      1      0.10  0.0958    2.30 0.015  0.780    
BMI         1      0.01  0.0094    0.23 0.001  0.870    
HLA         2      0.07  0.0342    0.82 0.011  0.619    
T1Dstatus   1      0.02  0.0203    0.49 0.003  0.695    
Carbs       1      0.19  0.1891    4.55 0.030  0.042 *  
Residuals 132      5.49  0.0416         0.863  0.288    
Total     143      6.36                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.6.6 Carbohydrate (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun      4      0.38  0.0943    2.34 0.067   0.89
Age         1      0.02  0.0231    0.57 0.004   0.98
Parity      1      0.13  0.1343    3.33 0.024   0.88
BMI         1      0.09  0.0883    2.19 0.016   0.41
HLA         2      0.06  0.0280    0.70 0.010   0.58
T1Dstatus   1      0.04  0.0435    1.08 0.008   0.33
Carbs       1      0.05  0.0501    1.24 0.009   0.29
Residuals 120      4.84  0.0403         0.862   0.81
Total     131      5.61                 1.000       

8.1.2.7 Fibre intake

8.1.2.7.1 Fibre interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                      2      0.17  0.0831    2.13 0.012   0.38
T1Dstatus                1      0.09  0.0930    2.38 0.007   0.32
Fiber                    1      0.02  0.0191    0.49 0.001   0.85
seqRun                   5      0.97  0.1949    5.00 0.072   0.40
Tri                      2      0.02  0.0090    0.23 0.001   0.81
Age                      1      0.03  0.0253    0.65 0.002   0.98
Parity                   1      0.11  0.1062    2.72 0.008   0.98
BMI                      1      0.06  0.0587    1.50 0.004   0.82
Fiber_Time_Interaction   1      0.02  0.0235    0.60 0.002   0.24
Residuals              310     12.09  0.0390         0.891   0.85
Total                  325     13.58                 1.000       
8.1.2.7.2 Fibre interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
HLA                      2      0.17  0.0831    2.15 0.012  0.401    
T1Dstatus                1      0.09  0.0930    2.40 0.007  0.285    
Fiber                    1      0.02  0.0191    0.49 0.001  0.839    
seqRun                   5      0.97  0.1949    5.03 0.072  0.426    
Tri                      2      0.02  0.0090    0.23 0.001  0.792    
Age                      1      0.03  0.0253    0.65 0.002  0.975    
Parity                   1      0.11  0.1062    2.74 0.008  0.985    
BMI                      1      0.06  0.0587    1.52 0.004  0.797    
Fiber_Time_Interaction   1      0.12  0.1158    2.99 0.009  0.001 ***
Residuals              310     12.00  0.0387         0.884  0.622    
Total                  325     13.58                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.7.3 Fibre interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2      0.17  0.0831    2.14 0.012  0.423  
T1Dstatus                1      0.09  0.0930    2.40 0.007  0.284  
Fiber                    1      0.02  0.0191    0.49 0.001  0.860  
seqRun                   5      0.97  0.1949    5.02 0.072  0.389  
Tri                      2      0.02  0.0090    0.23 0.001  0.832  
Age                      1      0.03  0.0253    0.65 0.002  0.967  
Parity                   1      0.11  0.1062    2.74 0.008  0.983  
BMI                      1      0.06  0.0587    1.51 0.004  0.807  
Fiber_Time_Interaction   1      0.08  0.0813    2.10 0.006  0.099 .
Residuals              310     12.03  0.0388         0.886  0.772  
Total                  325     13.58                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.7.4 Fibre (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun     3     0.158  0.0527   1.714 0.099  0.001 ***
Age        1     0.017  0.0171   0.555 0.011  0.001 ***
Parity     1     0.047  0.0466   1.518 0.029  0.001 ***
BMI        1     0.062  0.0622   2.024 0.039  0.001 ***
HLA        2     0.035  0.0173   0.562 0.022  0.721    
T1Dstatus  1     0.053  0.0527   1.714 0.033  0.173    
Fiber      1     0.025  0.0252   0.820 0.016  0.433    
Residuals 39     1.198  0.0307         0.751  0.513    
Total     49     1.595                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.7.5 Fibre (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun      4      0.42  0.1059   2.473 0.067  0.001 ***
Age         1      0.06  0.0632   1.477 0.010  0.561    
Parity      1      0.10  0.0958   2.237 0.015  0.762    
BMI         1      0.01  0.0094   0.220 0.001  0.827    
HLA         2      0.07  0.0342   0.799 0.011  0.604    
T1Dstatus   1      0.02  0.0203   0.474 0.003  0.657    
Fiber       1      0.03  0.0277   0.648 0.004  0.553    
Residuals 132      5.65  0.0428         0.889  0.803    
Total     143      6.36                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.7.6 Fibre (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      4      0.38  0.0943    2.38 0.067  0.850  
Age         1      0.02  0.0231    0.58 0.004  0.979  
Parity      1      0.13  0.1343    3.38 0.024  0.870  
BMI         1      0.09  0.0883    2.22 0.016  0.444  
HLA         2      0.06  0.0280    0.71 0.010  0.586  
T1Dstatus   1      0.04  0.0435    1.10 0.008  0.345  
Fiber       1      0.12  0.1214    3.06 0.022  0.072 .
Residuals 120      4.76  0.0397         0.850  0.551  
Total     131      5.61                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

8.1.2.8 1,5-AG (glucose control measurement)

8.1.2.8.1 1,5-AG interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2      0.16  0.0814    2.06 0.012  0.392  
T1Dstatus              1      0.06  0.0646    1.63 0.005  0.429  
Days                   1      0.09  0.0908    2.29 0.007  0.031 *
seqRun                 4      0.73  0.1826    4.61 0.054  0.362  
Age                    1      0.03  0.0287    0.72 0.002  0.234  
Parity                 1      0.10  0.0960    2.42 0.007  0.960  
BMI                    1      0.11  0.1081    2.73 0.008  0.745  
AG15                   1      0.04  0.0389    0.98 0.003  0.150  
AG15_T1D_Interaction   1      0.01  0.0105    0.27 0.001  0.912  
Residuals            311     12.31  0.0396         0.902  0.441  
Total                324     13.64                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.8.2 1,5-AG within T1D women

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.07  0.0327    0.96 0.008  0.715  
Days        1      0.06  0.0583    1.71 0.007  0.025 *
seqRun      4      0.67  0.1671    4.91 0.084  0.611  
Age         1      0.02  0.0187    0.55 0.002  0.981  
Parity      1      0.09  0.0894    2.63 0.011  0.896  
BMI         1      0.14  0.1394    4.10 0.018  0.217  
AG15        1      0.02  0.0202    0.59 0.003  0.375  
Residuals 202      6.87  0.0340         0.866  0.662  
Total     213      7.93                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
8.1.2.8.3 1,5-AG interaction with time (within non-T1D women)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.29  0.1435   2.853 0.051   0.27
Days        1      0.04  0.0358   0.712 0.006   0.49
seqRun      3      0.19  0.0618   1.230 0.033   0.77
Age         1      0.03  0.0304   0.605 0.005   0.25
Parity      1      0.04  0.0440   0.875 0.008   0.18
BMI         1      0.01  0.0076   0.151 0.001   0.67
AG15        1      0.04  0.0373   0.743 0.007   0.85
Residuals 100      5.03  0.0503         0.889   0.43
Total     110      5.66                 1.000       
8.1.2.8.4 1,5-AG (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.16  0.0814    2.06 0.012  0.393  
T1Dstatus   1      0.06  0.0646    1.63 0.005  0.427  
Days        1      0.09  0.0908    2.30 0.007  0.032 *
seqRun      4      0.73  0.1826    4.62 0.054  0.357  
Age         1      0.03  0.0287    0.73 0.002  0.222  
Parity      1      0.10  0.0960    2.43 0.007  0.954  
BMI         1      0.11  0.1081    2.74 0.008  0.780  
AG15        1      0.04  0.0389    0.98 0.003  0.121  
Residuals 312     12.32  0.0395         0.903  0.406  
Total     324     13.64                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

8.1.2.9 Pre-eclampsia (within T1D women)


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

              Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA            2      0.07  0.0341    1.01 0.008   0.71
Days           1      0.03  0.0334    0.99 0.004   0.12
seqRun         4      0.87  0.2164    6.42 0.098   0.46
Age            1      0.02  0.0214    0.63 0.002   0.99
Parity         1      0.11  0.1112    3.30 0.013   0.81
BMI            1      0.13  0.1282    3.81 0.015   0.22
Preeclampsia   1      0.06  0.0629    1.87 0.007   0.64
Residuals    223      7.51  0.0337         0.853   0.75
Total        234      8.80                 1.000       

8.2 Differential abundance analysis Order taxonomic level

Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type

       nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down               0  0  0  0        0        0        1         0         0         0
NotSig            23 23 23 23       22       23       20        23        23        22
Up                 0  0  0  0        1        0        2         0         0         1
       noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down             0           0           0
NotSig          23          23          23
Up               0           0           0

8.2.1 Across all trimesters (T1D vs non-T1D)

[1] "No DA taxa"

8.2.2 Only Trimester 1 (nonT1D vs T1D)

[1] "No DA taxa"

8.2.3 Only Trimester 2 (nonT1D vs T1D)

[1] "No DA taxa"

After filtering low prevalent taxa, no species was significantly different between T1D and non-T1D women in this comparison.

8.2.4 Only Trimester 3 (nonT1D vs T1D)

[1] "No DA taxa"

8.2.5 T1 vs T2 (T1D and non-T1D data)

       Classification LogFC   P.Val adj.P.Val mean% Prev%
1 Gammaproteobacteria  0.78 0.00202    0.0464 0.088  33.9
2 Gammaproteobacteria  0.78 0.00202    0.0464 0.083  31.6
3 Gammaproteobacteria  0.78 0.00202    0.0464 0.061  27.1

8.2.6 T2 vs T3 (T1D and non-T1D data)

[1] "No DA taxa"

Nothing left after filtering by prevalence and LogFC

8.2.7 T1 vs T3 (T1D and non-T1D data)

  Classification  LogFC   P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev% T3:mean%
1        Bacilli -0.807 0.00211    0.0243    0.169    55.4    0.268    63.3    0.355
  T3Prev%
1    71.4

8.2.8 T1 vs T2 (in women with T1D)

[1] "No DA taxa"

8.2.9 T2 vs T3 (in women with T1D)

[1] "No DA taxa"

8.2.10 T1 vs T3 (in women with T1D)

[1] Classification LogFC          P.Val          adj.P.Val      T1:mean%      
[6] T1Prev%        T3:mean%       T3Prev%       
<0 rows> (or 0-length row.names)

8.2.11 T1 vs T2 (in women without T1D)

[1] "No DA taxa"

8.2.12 T2 vs T3 (in women without T1D)

[1] "No DA taxa"

8.2.13 T1 vs T3 (in women without T1D)

[1] "No DA taxa"

9 Phylum taxonomic level

9.1 Microbial community composition analysis at Phylum level (Beta diversity analysis)

9.1.1 Interaction between T1D status and Time


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun                 5      0.84  0.1678    4.59 0.061   0.79  
Days                   1      0.10  0.0998    2.73 0.007   0.09 .
T1D_Time_Interaction   1      0.06  0.0557    1.52 0.004   0.16  
Age                    1      0.02  0.0180    0.49 0.001   0.48  
Parity                 1      0.15  0.1504    4.11 0.011   0.98  
BMI                    1      0.11  0.1109    3.03 0.008   0.61  
HLA                    2      0.11  0.0561    1.53 0.008   0.46  
T1Dstatus              1      0.01  0.0061    0.17 0.000   0.93  
Residuals            340     12.44  0.0366         0.899   0.73  
Total                353     13.83                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
[1] 0.157

9.1.2 Other factors

9.1.2.1 Age at conception

9.1.2.1.1 Age at conception interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.15 0.011   0.36
T1Dstatus              1      0.04  0.0436    1.20 0.003   0.52
seqRun                 5      0.85  0.1697    4.65 0.061   0.67
Tri                    2      0.07  0.0347    0.95 0.005   0.16
Age                    1      0.02  0.0169    0.46 0.001   0.89
Parity                 1      0.13  0.1302    3.57 0.009   0.98
BMI                    1      0.10  0.0996    2.73 0.007   0.80
Age_Time_Interaction   1      0.10  0.1004    2.75 0.007   0.16
Residuals            339     12.36  0.0365         0.894   0.64
Total                353     13.83                 1.000       
9.1.2.1.2 Age at conception interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.15 0.011   0.39
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.51
seqRun                 5      0.85  0.1697    4.65 0.061   0.64
Tri                    2      0.07  0.0347    0.95 0.005   0.18
Age                    1      0.02  0.0169    0.46 0.001   0.86
Parity                 1      0.13  0.1302    3.57 0.009   0.98
BMI                    1      0.10  0.0996    2.73 0.007   0.79
Age_Time_Interaction   1      0.09  0.0892    2.44 0.006   0.18
Residuals            339     12.38  0.0365         0.895   0.65
Total                353     13.83                 1.000       
9.1.2.1.3 Age at conception interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.13 0.011   0.36
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.49
seqRun                 5      0.85  0.1697    4.62 0.061   0.65
Tri                    2      0.07  0.0347    0.95 0.005   0.16
Age                    1      0.02  0.0169    0.46 0.001   0.85
Parity                 1      0.13  0.1302    3.54 0.009   0.98
BMI                    1      0.10  0.0996    2.71 0.007   0.80
Age_Time_Interaction   1      0.01  0.0073    0.20 0.001   0.66
Residuals            339     12.46  0.0367         0.901   0.78
Total                353     13.83                 1.000       
9.1.2.1.4 Age at conception (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.16  0.0783    2.14 0.011   0.36
T1Dstatus   1      0.04  0.0436    1.19 0.003   0.49
seqRun      5      0.85  0.1697    4.63 0.061   0.67
Tri         2      0.07  0.0347    0.95 0.005   0.18
Parity      1      0.13  0.1302    3.55 0.009   0.98
BMI         1      0.10  0.0989    2.70 0.007   0.81
Age         1      0.02  0.0176    0.48 0.001   0.34
Residuals 340     12.46  0.0367         0.901   0.78
Total     353     13.83                 1.000       

9.1.2.2 Body max index (BMI)

9.1.2.2.1 BMI interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.13 0.011   0.38
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.49
seqRun                 5      0.85  0.1697    4.62 0.061   0.68
Tri                    2      0.07  0.0347    0.95 0.005   0.16
Age                    1      0.02  0.0169    0.46 0.001   0.88
Parity                 1      0.13  0.1302    3.54 0.009   0.98
BMI                    1      0.10  0.0996    2.71 0.007   0.77
BMI_Time_Interaction   1      0.01  0.0061    0.17 0.000   0.88
Residuals            339     12.46  0.0368         0.901   0.85
Total                353     13.83                 1.000       
9.1.2.2.2 BMI interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.34
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.51
seqRun                 5      0.85  0.1697    4.63 0.061   0.65
Tri                    2      0.07  0.0347    0.95 0.005   0.17
Age                    1      0.02  0.0169    0.46 0.001   0.88
Parity                 1      0.13  0.1302    3.55 0.009   0.98
BMI                    1      0.10  0.0996    2.72 0.007   0.80
BMI_Time_Interaction   1      0.04  0.0411    1.12 0.003   0.54
Residuals            339     12.42  0.0366         0.898   0.78
Total                353     13.83                 1.000       
9.1.2.2.3 BMI (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.40
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.45
seqRun                 5      0.85  0.1697    4.63 0.061   0.63
Tri                    2      0.07  0.0347    0.95 0.005   0.18
Age                    1      0.02  0.0169    0.46 0.001   0.86
Parity                 1      0.13  0.1302    3.55 0.009   0.98
BMI                    1      0.10  0.0996    2.72 0.007   0.80
BMI_Time_Interaction   1      0.04  0.0351    0.96 0.003   0.15
Residuals            339     12.43  0.0367         0.899   0.73
Total                353     13.83                 1.000       
9.1.2.2.4 BMI (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.16  0.0783    2.14 0.011   0.38
T1Dstatus   1      0.04  0.0436    1.19 0.003   0.51
seqRun      5      0.85  0.1697    4.63 0.061   0.65
Tri         2      0.07  0.0347    0.95 0.005   0.17
Age         1      0.02  0.0169    0.46 0.001   0.88
Parity      1      0.13  0.1302    3.55 0.009   0.97
BMI         1      0.10  0.0996    2.72 0.007   0.79
Residuals 340     12.46  0.0367         0.901   0.76
Total     353     13.83                 1.000       

9.1.2.3 HLA type

9.1.2.3.1 HLA type interaction with time (reference: DR34 )

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.37
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.50
Days                   1      0.07  0.0747    2.04 0.005   0.11
seqRun                 5      0.88  0.1760    4.81 0.064   0.56
Age                    1      0.02  0.0163    0.44 0.001   0.89
Parity                 1      0.13  0.1250    3.42 0.009   0.98
BMI                    1      0.10  0.0955    2.61 0.007   0.87
HLA_Time_Interaction   1      0.01  0.0098    0.27 0.001   0.99
Residuals            340     12.43  0.0366         0.899   0.81
Total                353     13.83                 1.000       
9.1.2.3.2 HLA type interaction with time (reference: DRXX)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.35
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.52
Days                   1      0.07  0.0747    2.04 0.005   0.13
seqRun                 5      0.88  0.1760    4.81 0.064   0.58
Age                    1      0.02  0.0163    0.44 0.001   0.90
Parity                 1      0.13  0.1250    3.42 0.009   0.97
BMI                    1      0.10  0.0955    2.61 0.007   0.85
HLA_Time_Interaction   1      0.00  0.0018    0.05 0.000   1.00
Residuals            340     12.44  0.0366         0.899   0.75
Total                353     13.83                 1.000       
9.1.2.3.3 HLA type interaction with time (reference: Group3o4)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.38
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.51
Days                   1      0.07  0.0747    2.04 0.005   0.13
seqRun                 5      0.88  0.1760    4.81 0.064   0.56
Age                    1      0.02  0.0163    0.44 0.001   0.90
Parity                 1      0.13  0.1250    3.42 0.009   0.98
BMI                    1      0.10  0.0955    2.61 0.007   0.85
HLA_Time_Interaction   1      0.01  0.0090    0.25 0.001   1.00
Residuals            340     12.43  0.0366         0.899   0.81
Total                353     13.83                 1.000       
9.1.2.3.4 HLA type (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
Days        1      0.08  0.0779    2.14 0.006   0.12
seqRun      5      0.86  0.1722    4.72 0.062   0.74
Age         1      0.02  0.0208    0.57 0.002   0.43
Parity      1      0.17  0.1673    4.59 0.012   0.93
BMI         1      0.12  0.1202    3.29 0.009   0.39
T1Dstatus   1      0.03  0.0303    0.83 0.002   0.58
HLA         2      0.11  0.0572    1.57 0.008   0.50
Residuals 341     12.44  0.0365         0.899   0.71
Total     353     13.83                 1.000       

9.1.2.4 Parity

9.1.2.4.1 Parity interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                         Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                       2      0.16  0.0783    2.15 0.011  0.356  
T1Dstatus                 1      0.04  0.0436    1.20 0.003  0.477  
Days                      1      0.07  0.0747    2.05 0.005  0.128  
seqRun                    5      0.88  0.1760    4.83 0.064  0.565  
Age                       1      0.02  0.0163    0.45 0.001  0.905  
Parity                    1      0.13  0.1250    3.43 0.009  0.976  
BMI                       1      0.10  0.0955    2.62 0.007  0.856  
Parity_Time_Interaction   1      0.04  0.0449    1.23 0.003  0.088 .
Residuals               340     12.39  0.0365         0.896  0.587  
Total                   353     13.83                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.4.2 Parity (no interaction but within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA        2     0.025  0.0124   0.376 0.014   0.78
T1Dstatus  1     0.003  0.0033   0.102 0.002   0.94
seqRun     1     0.032  0.0325   0.986 0.018   0.21
Age        1     0.093  0.0929   2.819 0.052   0.31
BMI        1     0.020  0.0198   0.601 0.011   0.72
Parity     1     0.037  0.0366   1.111 0.020   0.12
Residuals 48     1.581  0.0329         0.883   0.83
Total     55     1.791                 1.000       
9.1.2.4.3 Parity (no interaction but within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.10   0.048    1.22 0.015   0.43
T1Dstatus   1      0.02   0.018    0.46 0.003   0.68
seqRun      1      0.33   0.329    8.41 0.051   0.40
Age         1      0.03   0.026    0.68 0.004   0.96
BMI         1      0.02   0.015    0.39 0.002   0.21
Parity      1      0.06   0.062    1.58 0.010   0.94
Residuals 150      5.87   0.039         0.915   0.86
Total     157      6.41                 1.000       
9.1.2.4.4 Parity (no interaction but within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.10   0.050    1.37 0.018  0.302  
T1Dstatus   1      0.03   0.030    0.82 0.005  0.407  
seqRun      1      0.38   0.378   10.36 0.068  0.632  
Age         1      0.01   0.014    0.38 0.002  0.031 *
BMI         1      0.07   0.069    1.90 0.012  0.793  
Parity      1      0.18   0.184    5.05 0.033  0.899  
Residuals 132      4.81   0.036         0.861  0.656  
Total     139      5.59                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

9.1.2.5 Mode of delivery

9.1.2.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.37
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.48
MOD                    2      0.10  0.0485    1.33 0.007   0.58
Days                   1      0.08  0.0780    2.13 0.006   0.11
seqRun                 5      0.85  0.1699    4.64 0.061   0.67
Age                    1      0.03  0.0296    0.81 0.002   0.13
Parity                 1      0.12  0.1235    3.37 0.009   0.94
BMI                    1      0.07  0.0651    1.78 0.005   0.95
MOD_Time_Interaction   1      0.02  0.0150    0.41 0.001   0.65
Residuals            338     12.37  0.0366         0.895   0.83
Total                353     13.83                 1.000       
9.1.2.5.2 Mode of delivery interaction with time (reference: Elective caesarea)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.38
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.52
MOD                    2      0.10  0.0485    1.32 0.007   0.59
Days                   1      0.08  0.0780    2.13 0.006   0.12
seqRun                 5      0.85  0.1699    4.64 0.061   0.66
Age                    1      0.03  0.0296    0.81 0.002   0.12
Parity                 1      0.12  0.1235    3.37 0.009   0.95
BMI                    1      0.07  0.0651    1.78 0.005   0.96
MOD_Time_Interaction   1      0.01  0.0118    0.32 0.001   0.63
Residuals            338     12.37  0.0366         0.895   0.82
Total                353     13.83                 1.000       
9.1.2.5.3 Mode of delivery interaction with time (reference: Labour)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                    2      0.16  0.0783    2.14 0.011   0.36
T1Dstatus              1      0.04  0.0436    1.19 0.003   0.52
MOD                    2      0.10  0.0485    1.32 0.007   0.58
Days                   1      0.08  0.0780    2.13 0.006   0.12
seqRun                 5      0.85  0.1699    4.64 0.061   0.65
Age                    1      0.03  0.0296    0.81 0.002   0.10
Parity                 1      0.12  0.1235    3.37 0.009   0.95
BMI                    1      0.07  0.0651    1.78 0.005   0.96
MOD_Time_Interaction   1      0.00  0.0024    0.07 0.000   1.00
Residuals            338     12.38  0.0366         0.895   0.86
Total                353     13.83                 1.000       
9.1.2.5.4 Mode of delivery (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
Days        1      0.08  0.0779    2.13 0.006   0.11
seqRun      5      0.86  0.1722    4.71 0.062   0.73
Age         1      0.02  0.0208    0.57 0.002   0.44
Parity      1      0.17  0.1673    4.58 0.012   0.93
BMI         1      0.12  0.1202    3.29 0.009   0.38
HLA         2      0.10  0.0516    1.41 0.007   0.53
T1Dstatus   1      0.04  0.0416    1.14 0.003   0.47
MOD         2      0.05  0.0256    0.70 0.004   0.77
Residuals 339     12.39  0.0365         0.896   0.83
Total     353     13.83                 1.000       

9.1.2.6 Carbohydrate intake

9.1.2.6.1 Carbohydrate interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                     2      0.17  0.0862    2.40 0.014   0.33
T1Dstatus               1      0.07  0.0725    2.02 0.006   0.33
Carbs                   1      0.08  0.0759    2.11 0.006   0.33
seqRun                  5      0.81  0.1623    4.52 0.065   0.78
Tri                     2      0.02  0.0086    0.24 0.001   0.72
Age                     1      0.02  0.0220    0.61 0.002   0.98
Parity                  1      0.15  0.1522    4.24 0.012   0.92
BMI                     1      0.05  0.0539    1.50 0.004   0.89
Carb_Time_Interaction   1      0.00 -0.0035   -0.10 0.000   1.00
Residuals             310     11.14  0.0359         0.890   0.90
Total                 325     12.51                 1.000       
9.1.2.6.2 Carbohydrate interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2      0.17  0.0862    2.44 0.014  0.324   
T1Dstatus               1      0.07  0.0725    2.05 0.006  0.355   
Carbs                   1      0.08  0.0759    2.14 0.006  0.316   
seqRun                  5      0.81  0.1623    4.59 0.065  0.819   
Tri                     2      0.02  0.0086    0.24 0.001  0.735   
Age                     1      0.02  0.0220    0.62 0.002  0.982   
Parity                  1      0.15  0.1522    4.30 0.012  0.919   
BMI                     1      0.05  0.0539    1.53 0.004  0.884   
Carb_Time_Interaction   1      0.17  0.1693    4.79 0.014  0.002 **
Residuals             310     10.97  0.0354         0.876  0.554   
Total                 325     12.51                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.6.3 Carbohydrate interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                       Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                     2      0.17  0.0862    2.42 0.014  0.351   
T1Dstatus               1      0.07  0.0725    2.04 0.006  0.346   
Carbs                   1      0.08  0.0759    2.13 0.006  0.339   
seqRun                  5      0.81  0.1623    4.57 0.065  0.806   
Tri                     2      0.02  0.0086    0.24 0.001  0.708   
Age                     1      0.02  0.0220    0.62 0.002  0.982   
Parity                  1      0.15  0.1522    4.28 0.012  0.912   
BMI                     1      0.05  0.0539    1.52 0.004  0.880   
Carb_Time_Interaction   1      0.12  0.1178    3.31 0.009  0.003 **
Residuals             310     11.02  0.0355         0.880  0.660   
Total                 325     12.51                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.6.4 Carbohydrate (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun     3     0.144  0.0479   1.746 0.104   0.75
Age        1     0.015  0.0153   0.557 0.011   0.75
Parity     1     0.041  0.0410   1.495 0.030   0.75
BMI        1     0.064  0.0645   2.351 0.047   0.75
HLA        2     0.020  0.0102   0.372 0.015   0.79
T1Dstatus  1     0.028  0.0281   1.024 0.020   0.32
Carbs      1     0.003  0.0026   0.095 0.002   0.93
Residuals 39     1.070  0.0274         0.772   0.86
Total     49     1.386                 1.000       
9.1.2.6.5 Carbohydrate (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
seqRun      4      0.38  0.0948    2.47 0.064  0.002 **
Age         1      0.06  0.0624    1.63 0.011  0.591   
Parity      1      0.12  0.1156    3.01 0.020  0.825   
BMI         1      0.01  0.0120    0.31 0.002  0.512   
HLA         2      0.06  0.0285    0.74 0.010  0.635   
T1Dstatus   1      0.01  0.0145    0.38 0.002  0.729   
Carbs       1      0.18  0.1823    4.75 0.031  0.041 * 
Residuals 132      5.07  0.0384         0.860  0.294   
Total     143      5.89                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.6.6 Carbohydrate (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
seqRun      4      0.36  0.0896    2.39 0.069   0.72
Age         1      0.02  0.0214    0.57 0.004   0.98
Parity      1      0.13  0.1286    3.43 0.025   0.87
BMI         1      0.08  0.0792    2.11 0.015   0.41
HLA         2      0.06  0.0279    0.74 0.011   0.54
T1Dstatus   1      0.03  0.0322    0.86 0.006   0.39
Carbs       1      0.05  0.0495    1.32 0.009   0.27
Residuals 120      4.50  0.0375         0.861   0.81
Total     131      5.23                 1.000       

9.1.2.7 Fibre intake

9.1.2.7.1 Fibre interaction with time (reference: trimester 1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA                      2      0.17  0.0862    2.40 0.014   0.33
T1Dstatus                1      0.07  0.0725    2.02 0.006   0.36
Fiber                    1      0.00  0.0038    0.11 0.000   0.96
seqRun                   5      0.90  0.1809    5.04 0.072   0.43
Tri                      2      0.02  0.0083    0.23 0.001   0.71
Age                      1      0.02  0.0215    0.60 0.002   0.99
Parity                   1      0.12  0.1207    3.37 0.010   0.99
BMI                      1      0.06  0.0618    1.72 0.005   0.80
Fiber_Time_Interaction   1      0.02  0.0193    0.54 0.002   0.22
Residuals              310     11.12  0.0359         0.889   0.88
Total                  325     12.51                 1.000       
9.1.2.7.2 Fibre interaction with time (reference: trimester 2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
HLA                      2      0.17  0.0862    2.42 0.014  0.345   
T1Dstatus                1      0.07  0.0725    2.04 0.006  0.352   
Fiber                    1      0.00  0.0038    0.11 0.000  0.971   
seqRun                   5      0.90  0.1809    5.08 0.072  0.452   
Tri                      2      0.02  0.0083    0.23 0.001  0.701   
Age                      1      0.02  0.0215    0.60 0.002  0.985   
Parity                   1      0.12  0.1207    3.39 0.010  0.991   
BMI                      1      0.06  0.0618    1.74 0.005  0.772   
Fiber_Time_Interaction   1      0.10  0.1044    2.93 0.008  0.002 **
Residuals              310     11.03  0.0356         0.882  0.691   
Total                  325     12.51                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.7.3 Fibre interaction with time (reference: trimester 3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                        Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                      2      0.17  0.0862    2.42 0.014  0.364  
T1Dstatus                1      0.07  0.0725    2.03 0.006  0.335  
Fiber                    1      0.00  0.0038    0.11 0.000  0.971  
seqRun                   5      0.90  0.1809    5.07 0.072  0.414  
Tri                      2      0.02  0.0083    0.23 0.001  0.745  
Age                      1      0.02  0.0215    0.60 0.002  0.978  
Parity                   1      0.12  0.1207    3.38 0.010  0.987  
BMI                      1      0.06  0.0618    1.73 0.005  0.782  
Fiber_Time_Interaction   1      0.08  0.0804    2.26 0.006  0.075 .
Residuals              310     11.06  0.0357         0.884  0.797  
Total                  325     12.51                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.7.4 Fibre (no interaction within T1)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

          Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)   
seqRun     3     0.144  0.0479   1.745 0.104  0.006 **
Age        1     0.015  0.0153   0.557 0.011  0.006 **
Parity     1     0.041  0.0410   1.495 0.030  0.006 **
BMI        1     0.064  0.0645   2.350 0.047  0.006 **
HLA        2     0.020  0.0102   0.372 0.015  0.797   
T1Dstatus  1     0.028  0.0281   1.023 0.020  0.325   
Fiber      1     0.002  0.0023   0.083 0.002  0.934   
Residuals 39     1.070  0.0274         0.772  0.829   
Total     49     1.386                 1.000          
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.7.5 Fibre (no interaction within T2)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
seqRun      4      0.38  0.0948   2.392 0.064  0.001 ***
Age         1      0.06  0.0624   1.573 0.011  0.561    
Parity      1      0.12  0.1156   2.916 0.020  0.845    
BMI         1      0.01  0.0120   0.303 0.002  0.514    
HLA         2      0.06  0.0285   0.718 0.010  0.622    
T1Dstatus   1      0.01  0.0145   0.366 0.002  0.705    
Fiber       1      0.01  0.0145   0.367 0.002  0.721    
Residuals 132      5.23  0.0396         0.889  0.869    
Total     143      5.89                 1.000           
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.7.6 Fibre (no interaction within T3)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
seqRun      4      0.36  0.0896    2.43 0.069  0.658  
Age         1      0.02  0.0214    0.58 0.004  0.975  
Parity      1      0.13  0.1286    3.48 0.025  0.846  
BMI         1      0.08  0.0792    2.14 0.015  0.440  
HLA         2      0.06  0.0279    0.75 0.011  0.541  
T1Dstatus   1      0.03  0.0322    0.87 0.006  0.404  
Fiber       1      0.12  0.1151    3.11 0.022  0.074 .
Residuals 120      4.44  0.0370         0.849  0.572  
Total     131      5.23                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

9.1.2.8 1,5-AG (glucose control measurement)

9.1.2.8.1 1,5-AG interaction with time

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

                      Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA                    2      0.18  0.0883    2.42 0.014  0.318  
T1Dstatus              1      0.05  0.0462    1.26 0.004  0.509  
Days                   1      0.10  0.0982    2.69 0.008  0.028 *
seqRun                 4      0.67  0.1677    4.59 0.053  0.393  
Age                    1      0.01  0.0135    0.37 0.001  0.636  
Parity                 1      0.11  0.1118    3.06 0.009  0.975  
BMI                    1      0.11  0.1111    3.04 0.009  0.731  
AG15                   1      0.03  0.0312    0.85 0.002  0.061 .
AG15_T1D_Interaction   1      0.01  0.0101    0.28 0.001  0.839  
Residuals            311     11.37  0.0366         0.900  0.403  
Total                324     12.64                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.8.2 1,5-AG within T1D women

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.07  0.0355    1.15 0.010  0.591  
Days        1      0.06  0.0611    1.97 0.008  0.017 *
seqRun      4      0.62  0.1558    5.03 0.086  0.646  
Age         1      0.00  0.0049    0.16 0.001  0.963  
Parity      1      0.10  0.1028    3.32 0.014  0.881  
BMI         1      0.14  0.1427    4.61 0.020  0.203  
AG15        1      0.02  0.0162    0.52 0.002  0.360  
Residuals 202      6.25  0.0309         0.860  0.536  
Total     213      7.27                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
9.1.2.8.3 1,5-AG interaction with time (within non-T1D women)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)
HLA         2      0.26  0.1302   2.723 0.049   0.29
Days        1      0.04  0.0369   0.772 0.007   0.47
seqRun      3      0.15  0.0513   1.072 0.029   0.64
Age         1      0.03  0.0276   0.577 0.005   0.23
Parity      1      0.04  0.0366   0.765 0.007   0.51
BMI         1      0.01  0.0064   0.133 0.001   0.68
AG15        1      0.03  0.0314   0.656 0.006   0.87
Residuals 100      4.78  0.0478         0.896   0.46
Total     110      5.33                 1.000       
9.1.2.8.4 1,5-AG (no interaction)

Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA         2      0.18  0.0883    2.42 0.014  0.323  
T1Dstatus   1      0.05  0.0462    1.27 0.004  0.496  
Days        1      0.10  0.0982    2.69 0.008  0.030 *
seqRun      4      0.67  0.1677    4.60 0.053  0.383  
Age         1      0.01  0.0135    0.37 0.001  0.665  
Parity      1      0.11  0.1118    3.06 0.009  0.977  
BMI         1      0.11  0.1111    3.05 0.009  0.764  
AG15        1      0.03  0.0312    0.85 0.002  0.058 .
Residuals 312     11.38  0.0365         0.900  0.362  
Total     324     12.64                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

9.1.2.9 Pre-eclampsia (within T1D women)


Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F],      permutations = 0) 

Permutation: free
Number of permutations: 0

Terms added sequentially (first to last)

              Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)  
HLA            2      0.08  0.0389    1.27 0.010   0.61  
Days           1      0.04  0.0357    1.17 0.004   0.09 .
seqRun         4      0.81  0.2031    6.63 0.101   0.51  
Age            1      0.01  0.0082    0.27 0.001   0.99  
Parity         1      0.13  0.1284    4.20 0.016   0.79  
BMI            1      0.13  0.1316    4.30 0.016   0.20  
Preeclampsia   1      0.06  0.0571    1.86 0.007   0.63  
Residuals    223      6.83  0.0306         0.845   0.65  
Total        234      8.08                 1.000         
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

9.2 Differential abundance analysis Phylum taxonomic level

Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type

       nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down               0  0  0  0        0        0        0         1         0         1
NotSig            11 11 11 11       11       11       11        10        11        10
Up                 0  0  0  0        0        0        0         0         0         0
       noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down             0           0           0
NotSig          11          11          11
Up               0           0           0

9.2.1 Across all trimesters (T1D vs non-T1D)

[1] "No DA taxa"

9.2.2 Only Trimester 1 (nonT1D vs T1D)

[1] "No DA taxa"

9.2.3 Only Trimester 2 (nonT1D vs T1D)

[1] "No DA taxa"

After filtering low prevalent taxa, no species was significantly different between T1D and non-T1D women in this comparison.

9.2.4 Only Trimester 3 (nonT1D vs T1D)

[1] "No DA taxa"

9.2.5 T1 vs T2 (T1D and non-T1D data)

[1] "No DA taxa"

9.2.6 T2 vs T3 (T1D and non-T1D data)

[1] "No DA taxa"

Nothing left after filtering by prevalence and LogFC

9.2.7 T1 vs T3 (T1D and non-T1D data)

[1] "No DA taxa"

9.2.8 T1 vs T2 (in women with T1D)

  Classification  LogFC    P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1  Bacteroidetes -0.634 0.000461   0.00507     52.3    97.4     55.1     100

9.2.9 T2 vs T3 (in women with T1D)

[1] "No DA taxa"

9.2.10 T1 vs T3 (in women with T1D)

  Classification  LogFC   P.Val adj.P.Val mean% Prev%
1  Bacteroidetes -0.589 0.00113    0.0124  52.3  97.4
2  Bacteroidetes -0.589 0.00113    0.0124  55.9 100.0

9.2.11 T1 vs T2 (in women without T1D)

[1] "No DA taxa"

9.2.12 T2 vs T3 (in women without T1D)

[1] "No DA taxa"

9.2.13 T1 vs T3 (in women without T1D)

[1] "No DA taxa"